Own Every Moment at NetApp While professional experience and qualifications are key for this role, make sure to check you have the preferable soft skills before applying if required. At NetApp, your ideas power innovation. We lead in intelligent data infrastructure-delivering unified storage, integrated data services, and solutions that help organizations unlock the full potential of their data, from AI to multicloud. Ready to innovate and contribute to our path to $10B? Here, you'll collaborate with passionate teams, tackle real-world challenges, and see your impact in how customers transform and grow. If you're ready to bring curiosity, creativity, and drive to every moment, NetApp is where your journey begins. Job Summary NetApp is hiring a?principal-level product leader?to own the?AI product strategy?for?Azure NetApp Files (ANF)-a?first-party, fully managed enterprise file service on Microsoft Azure, delivered in deep partnership between NetApp and Microsoft. In the spirit of NetApp's?"business builder"?cloud roles, you will translate a fast-moving AI landscape into?differentiated platform capabilities,?joint roadmap bets?with Microsoft, and?enterprise outcomes?(performance, data locality, governance, and time-to-value for AI pipelines). You will sit at the intersection of?enterprise storage,?Azure AI infrastructure, and?industry AI workloads, ensuring ANF is positioned and built as a?strategic data foundation?for training, inference, RAG, analytics, simulation, and agentic workflows-without forcing customers to abandon enterprise file semantics, protection, or hybrid operating models. Role Overview We need a?highly strategic and deeply technical?principal PM who can: Define?multi-year AI vision and roadmap?for ANF in the context of Azure AI services, GPU estates, data platforms, and regulated enterprise environments. Turn emerging patterns (LLMs, RAG, agents, orchestration, multimodal data, vector retrieval, high-throughput checkpointing) into?concrete product requirements?and?joint go-to-market?narratives with Microsoft. Balance?hyperscaler co-development?constraints with?NetApp differentiation?(enterprise data services, multiprotocol access, lifecycle management, resiliency, and cross-cloud consistency where relevant). Responsibilities AI strategy & roadmap Own end-to-end?AI strategy?for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. Prioritize investments across?performance,?scale,?data services,?protocol and API surfaces, and?operational excellence?for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) RAG and enterprise search (datasets, versioning, clones, refresh patterns) Agentic workflows and orchestration (durable shared state, tool/data access patterns-where productized responsibly) Large multimodal and enterprise datasets (governance, access control, lifecycle) Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership Partner with?Microsoft?teams across?Azure AI / Foundry,?Azure Machine Learning,?AKS / container platforms,?GPU infrastructure,?data/analytics?(e.g. Databricks-style patterns on Azure), and core Azure storage/networking dependencies. Align ANF's AI story with?Azure-wide AI data?guidance and reference architectures, and feed?real customer workload evidence?back into joint planning. Cross-functional leadership Lead across?engineering, product marketing, sales, customer success, and professional services?to ship capabilities and repeatable?reference architectures / proof points. Engage?strategic customers?and?design partners?to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into?differentiated bets. Represent ANF as a?credible technical executive?in briefings, advisory councils, and industry forums. Industry segmentation Tailor AI storage strategy for segments where file semantics and performance matter, for example:?semiconductor/EDA,?manufacturing,?healthcare imaging,?financial services,?energy,?media & entertainment, and?HPC/simulation-including compliance and data residency realities. AI strategy & roadmap Own end-to-end?AI strategy?for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. Prioritize investments across?performance,?scale,?data services,?protocol and API surfaces, and?operational excellence?for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) RAG and enterprise search (datasets, versioning, clones, refresh patterns) Agentic workflows and orchestration (durable shared state, tool/data access patterns-where productized responsibly) Large multimodal and enterprise datasets (governance, access control, lifecycle) Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership Partner with?Microsoft?teams across?Azure AI / Foundry,?Azure Machine Learning,?AKS / container platforms,?GPU infrastructure,?data/analytics?(e.g. Databricks-style patterns on Azure), and core Azure storage/networking dependencies. Align ANF's AI story with?Azure-wide AI data?guidance and reference architectures, and feed?real customer workload evidence?back into joint planning. Cross-functional leadership Lead across?engineering, product marketing, sales, customer success, and professional services?to ship capabilities and repeatable?reference architectures / proof points. Engage?strategic customers?and?design partners?to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into?differentiated bets. Represent ANF as a?credible technical executive?in briefings, advisory councils, and industry forums. Industry segmentation Tailor AI storage strategy for segments where file semantics and performance matter, for example:?semiconductor/EDA,?manufacturing,?healthcare imaging,?financial services,?energy,?media & entertainment, and?HPC/simulation-including compliance and data residency realities. Job Requirements Required 10+ years?product management in?cloud infrastructure,?enterprise storage,?AI/ML infrastructure, or?data platforms?(principal scope: portfolio strategy, multi-team alignment, executive storytelling). Strong command of?enterprise storage: NFS/SMB semantics, snapshots/clones, replication, backup integration patterns, capacity/performance tiers, and large-scale filesystem behavior under parallel workloads. Hands-on familiarity with?modern AI stacks: LLMs, RAG architectures, embeddings/vector retrieval patterns, training vs. inference IO profiles, orchestration, and enterprise AI data pipelines. Demonstrated success influencing?engineering and partner roadmaps?without direct authority; experience with?hyperscaler first-party?or deeply partnered services is a strong plus. Excellent written and verbal communication to?customers, executives, and engineers. Preferred Direct experience with?Microsoft Azure?AI services,?GPU?estates on Azure, and/or?Azure Kubernetes Service?+ ML platform integrations. Familiarity with?Databricks,?Iceberg/Delta-class open table patterns,?Kubernetes?storage patterns,?NVIDIA AI?software stacks, and?enterprise MLOps?release cadences. Background in?regulated industries?and enterprise security/governance requirements for AI data. Education MBA?or advanced degree in?CS/Engineering?(helpful, not a substitute for demonstrated technical depth). Compensation: The target salary range for this position is $228,000 - $325,000. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off, various Leave options, Performance-Based Incentives, employee stock purchase plan, and/or restricted stocks (RSU's), with all offerings subject to regional variations and governed by local laws, regulations, and company policies. Benefits may vary by country and region, and further details will be provided as part of the recruitment process. At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in-office and/or in-person expectations, which will be shared during the recruitment process. Equal Opportunity Employer: . click apply for full job details
06/08/2026
Full time
Own Every Moment at NetApp While professional experience and qualifications are key for this role, make sure to check you have the preferable soft skills before applying if required. At NetApp, your ideas power innovation. We lead in intelligent data infrastructure-delivering unified storage, integrated data services, and solutions that help organizations unlock the full potential of their data, from AI to multicloud. Ready to innovate and contribute to our path to $10B? Here, you'll collaborate with passionate teams, tackle real-world challenges, and see your impact in how customers transform and grow. If you're ready to bring curiosity, creativity, and drive to every moment, NetApp is where your journey begins. Job Summary NetApp is hiring a?principal-level product leader?to own the?AI product strategy?for?Azure NetApp Files (ANF)-a?first-party, fully managed enterprise file service on Microsoft Azure, delivered in deep partnership between NetApp and Microsoft. In the spirit of NetApp's?"business builder"?cloud roles, you will translate a fast-moving AI landscape into?differentiated platform capabilities,?joint roadmap bets?with Microsoft, and?enterprise outcomes?(performance, data locality, governance, and time-to-value for AI pipelines). You will sit at the intersection of?enterprise storage,?Azure AI infrastructure, and?industry AI workloads, ensuring ANF is positioned and built as a?strategic data foundation?for training, inference, RAG, analytics, simulation, and agentic workflows-without forcing customers to abandon enterprise file semantics, protection, or hybrid operating models. Role Overview We need a?highly strategic and deeply technical?principal PM who can: Define?multi-year AI vision and roadmap?for ANF in the context of Azure AI services, GPU estates, data platforms, and regulated enterprise environments. Turn emerging patterns (LLMs, RAG, agents, orchestration, multimodal data, vector retrieval, high-throughput checkpointing) into?concrete product requirements?and?joint go-to-market?narratives with Microsoft. Balance?hyperscaler co-development?constraints with?NetApp differentiation?(enterprise data services, multiprotocol access, lifecycle management, resiliency, and cross-cloud consistency where relevant). Responsibilities AI strategy & roadmap Own end-to-end?AI strategy?for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. Prioritize investments across?performance,?scale,?data services,?protocol and API surfaces, and?operational excellence?for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) RAG and enterprise search (datasets, versioning, clones, refresh patterns) Agentic workflows and orchestration (durable shared state, tool/data access patterns-where productized responsibly) Large multimodal and enterprise datasets (governance, access control, lifecycle) Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership Partner with?Microsoft?teams across?Azure AI / Foundry,?Azure Machine Learning,?AKS / container platforms,?GPU infrastructure,?data/analytics?(e.g. Databricks-style patterns on Azure), and core Azure storage/networking dependencies. Align ANF's AI story with?Azure-wide AI data?guidance and reference architectures, and feed?real customer workload evidence?back into joint planning. Cross-functional leadership Lead across?engineering, product marketing, sales, customer success, and professional services?to ship capabilities and repeatable?reference architectures / proof points. Engage?strategic customers?and?design partners?to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into?differentiated bets. Represent ANF as a?credible technical executive?in briefings, advisory councils, and industry forums. Industry segmentation Tailor AI storage strategy for segments where file semantics and performance matter, for example:?semiconductor/EDA,?manufacturing,?healthcare imaging,?financial services,?energy,?media & entertainment, and?HPC/simulation-including compliance and data residency realities. AI strategy & roadmap Own end-to-end?AI strategy?for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. Prioritize investments across?performance,?scale,?data services,?protocol and API surfaces, and?operational excellence?for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) RAG and enterprise search (datasets, versioning, clones, refresh patterns) Agentic workflows and orchestration (durable shared state, tool/data access patterns-where productized responsibly) Large multimodal and enterprise datasets (governance, access control, lifecycle) Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership Partner with?Microsoft?teams across?Azure AI / Foundry,?Azure Machine Learning,?AKS / container platforms,?GPU infrastructure,?data/analytics?(e.g. Databricks-style patterns on Azure), and core Azure storage/networking dependencies. Align ANF's AI story with?Azure-wide AI data?guidance and reference architectures, and feed?real customer workload evidence?back into joint planning. Cross-functional leadership Lead across?engineering, product marketing, sales, customer success, and professional services?to ship capabilities and repeatable?reference architectures / proof points. Engage?strategic customers?and?design partners?to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into?differentiated bets. Represent ANF as a?credible technical executive?in briefings, advisory councils, and industry forums. Industry segmentation Tailor AI storage strategy for segments where file semantics and performance matter, for example:?semiconductor/EDA,?manufacturing,?healthcare imaging,?financial services,?energy,?media & entertainment, and?HPC/simulation-including compliance and data residency realities. Job Requirements Required 10+ years?product management in?cloud infrastructure,?enterprise storage,?AI/ML infrastructure, or?data platforms?(principal scope: portfolio strategy, multi-team alignment, executive storytelling). Strong command of?enterprise storage: NFS/SMB semantics, snapshots/clones, replication, backup integration patterns, capacity/performance tiers, and large-scale filesystem behavior under parallel workloads. Hands-on familiarity with?modern AI stacks: LLMs, RAG architectures, embeddings/vector retrieval patterns, training vs. inference IO profiles, orchestration, and enterprise AI data pipelines. Demonstrated success influencing?engineering and partner roadmaps?without direct authority; experience with?hyperscaler first-party?or deeply partnered services is a strong plus. Excellent written and verbal communication to?customers, executives, and engineers. Preferred Direct experience with?Microsoft Azure?AI services,?GPU?estates on Azure, and/or?Azure Kubernetes Service?+ ML platform integrations. Familiarity with?Databricks,?Iceberg/Delta-class open table patterns,?Kubernetes?storage patterns,?NVIDIA AI?software stacks, and?enterprise MLOps?release cadences. Background in?regulated industries?and enterprise security/governance requirements for AI data. Education MBA?or advanced degree in?CS/Engineering?(helpful, not a substitute for demonstrated technical depth). Compensation: The target salary range for this position is $228,000 - $325,000. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off, various Leave options, Performance-Based Incentives, employee stock purchase plan, and/or restricted stocks (RSU's), with all offerings subject to regional variations and governed by local laws, regulations, and company policies. Benefits may vary by country and region, and further details will be provided as part of the recruitment process. At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in-office and/or in-person expectations, which will be shared during the recruitment process. Equal Opportunity Employer: . click apply for full job details
Own Every Moment at NetApp At NetApp, your ideas power innovation. We lead in intelligent data infrastructure-delivering unified storage, integrated data services, and solutions that help organizations unlock the full potential of their data, from AI to multicloud. Ready to innovate and contribute to our path to $10B? Here, you'll collaborate with passionate teams, tackle real-world challenges, and see your impact in how customers transform and grow. If you're ready to bring curiosity, creativity, and drive to every moment, NetApp is where your journey begins. Job Summary NetApp is hiring a principal-level product leader to own the AI product strategy for Azure NetApp Files (ANF)-a first-party, fully managed enterprise file service on Microsoft Azure, delivered in deep partnership between NetApp and Microsoft. In the spirit of NetApp's "business builder" cloud roles, you will translate a fast-moving AI landscape into differentiated platform capabilities, joint roadmap bets with Microsoft, and enterprise outcomes (performance, data locality, governance, and time-to-value for AI pipelines). You will sit at the intersection of enterprise storage, Azure AI infrastructure, and industry AI workloads, ensuring ANF is positioned and built as a strategic data foundation for training, inference, RAG, analytics, simulation, and agentic workflows-without forcing customers to abandon enterprise file semantics, protection, or hybrid operating models. Role Overview We need a highly strategic and deeply technical principal PM who can: Define multi-year AI vision and roadmap for ANF in the context of Azure AI services, GPU estates, data platforms, and regulated enterprise environments. Turn emerging patterns (LLMs, RAG, agents, orchestration, multimodal data, vector retrieval, high-throughput checkpointing) into concrete product requirements and joint go-to-market narratives with Microsoft. Balance hyperscaler co-development constraints with NetApp differentiation (enterprise data services, multiprotocol access, lifecycle management, resiliency, and cross-cloud consistency where relevant). Responsibilities AI strategy & roadmap Own end-to-end AI strategy for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. Prioritize investments across performance, scale, data services, protocol and API surfaces, and operational excellence for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) RAG and enterprise search (datasets, versioning, clones, refresh patterns) Agentic workflows and orchestration (durable shared state, tool/data access patterns-where productized responsibly) Large multimodal and enterprise datasets (governance, access control, lifecycle) Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership Partner with Microsoft teams across Azure AI / Foundry, Azure Machine Learning, AKS / container platforms, GPU infrastructure, data/analytics (e.g. Databricks-style patterns on Azure), and core Azure storage/networking dependencies. Align ANF's AI story with Azure-wide AI data guidance and reference architectures, and feed real customer workload evidence back into joint planning. Cross-functional leadership Lead across engineering, product marketing, sales, customer success, and professional services to ship capabilities and repeatable reference architectures / proof points. Engage strategic customers and design partners to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into differentiated bets. Represent ANF as a credible technical executive in briefings, advisory councils, and industry forums. Industry segmentation Tailor AI storage strategy for segments where file semantics and performance matter, for example: semiconductor/EDA, manufacturing, healthcare imaging, financial services, energy, media & entertainment, and HPC/simulation-including compliance and data residency realities. AI strategy & roadmap Own end-to-end AI strategy for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. Prioritize investments across performance, scale, data services, protocol and API surfaces, and operational excellence for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) RAG and enterprise search (datasets, versioning, clones, refresh patterns) Agentic workflows and orchestration (durable shared state, tool/data access patterns-where productized responsibly) Large multimodal and enterprise datasets (governance, access control, lifecycle) Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership Partner with Microsoft teams across Azure AI / Foundry, Azure Machine Learning, AKS / container platforms, GPU infrastructure, data/analytics (e.g. Databricks-style patterns on Azure), and core Azure storage/networking dependencies. Align ANF's AI story with Azure-wide AI data guidance and reference architectures, and feed real customer workload evidence back into joint planning. Cross-functional leadership Lead across engineering, product marketing, sales, customer success, and professional services to ship capabilities and repeatable reference architectures / proof points. Engage strategic customers and design partners to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into differentiated bets. Represent ANF as a credible technical executive in briefings, advisory councils, and industry forums. Industry segmentation Tailor AI storage strategy for segments where file semantics and performance matter, for example: semiconductor/EDA, manufacturing, healthcare imaging, financial services, energy, media & entertainment, and HPC/simulation-including compliance and data residency realities. Job Requirements Required 10+ years product management in cloud infrastructure, enterprise storage, AI/ML infrastructure, or data platforms (principal scope: portfolio strategy, multi-team alignment, executive storytelling). Strong command of enterprise storage: NFS/SMB semantics, snapshots/clones, replication, backup integration patterns, capacity/performance tiers, and large-scale filesystem behavior under parallel workloads. Hands-on familiarity with modern AI stacks: LLMs, RAG architectures, embeddings/vector retrieval patterns, training vs. inference IO profiles, orchestration, and enterprise AI data pipelines. Demonstrated success influencing engineering and partner roadmaps without direct authority; experience with hyperscaler first-party or deeply partnered services is a strong plus. Excellent written and verbal communication to customers, executives, and engineers. Preferred Direct experience with Microsoft Azure AI services, GPU estates on Azure, and/or Azure Kubernetes Service + ML platform integrations. Familiarity with Databricks, Iceberg/Delta-class open table patterns, Kubernetes storage patterns, NVIDIA AI software stacks, and enterprise MLOps release cadences. Background in regulated industries and enterprise security/governance requirements for AI data. Education MBA or advanced degree in CS/Engineering (helpful, not a substitute for demonstrated technical depth). Compensation: The target salary range for this position is $228,000 - $325,000. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off, various Leave options, Performance-Based Incentives, employee stock purchase plan, and/or restricted stocks (RSU's), with all offerings subject to regional variations and governed by local laws, regulations, and company policies. Benefits may vary by country and region, and further details will be provided as part of the recruitment process. At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in-office and/or in-person expectations, which will be shared during the recruitment process. Equal Opportunity Employer: NetApp is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all federal . click apply for full job details
06/08/2026
Full time
Own Every Moment at NetApp At NetApp, your ideas power innovation. We lead in intelligent data infrastructure-delivering unified storage, integrated data services, and solutions that help organizations unlock the full potential of their data, from AI to multicloud. Ready to innovate and contribute to our path to $10B? Here, you'll collaborate with passionate teams, tackle real-world challenges, and see your impact in how customers transform and grow. If you're ready to bring curiosity, creativity, and drive to every moment, NetApp is where your journey begins. Job Summary NetApp is hiring a principal-level product leader to own the AI product strategy for Azure NetApp Files (ANF)-a first-party, fully managed enterprise file service on Microsoft Azure, delivered in deep partnership between NetApp and Microsoft. In the spirit of NetApp's "business builder" cloud roles, you will translate a fast-moving AI landscape into differentiated platform capabilities, joint roadmap bets with Microsoft, and enterprise outcomes (performance, data locality, governance, and time-to-value for AI pipelines). You will sit at the intersection of enterprise storage, Azure AI infrastructure, and industry AI workloads, ensuring ANF is positioned and built as a strategic data foundation for training, inference, RAG, analytics, simulation, and agentic workflows-without forcing customers to abandon enterprise file semantics, protection, or hybrid operating models. Role Overview We need a highly strategic and deeply technical principal PM who can: Define multi-year AI vision and roadmap for ANF in the context of Azure AI services, GPU estates, data platforms, and regulated enterprise environments. Turn emerging patterns (LLMs, RAG, agents, orchestration, multimodal data, vector retrieval, high-throughput checkpointing) into concrete product requirements and joint go-to-market narratives with Microsoft. Balance hyperscaler co-development constraints with NetApp differentiation (enterprise data services, multiprotocol access, lifecycle management, resiliency, and cross-cloud consistency where relevant). Responsibilities AI strategy & roadmap Own end-to-end AI strategy for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. Prioritize investments across performance, scale, data services, protocol and API surfaces, and operational excellence for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) RAG and enterprise search (datasets, versioning, clones, refresh patterns) Agentic workflows and orchestration (durable shared state, tool/data access patterns-where productized responsibly) Large multimodal and enterprise datasets (governance, access control, lifecycle) Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership Partner with Microsoft teams across Azure AI / Foundry, Azure Machine Learning, AKS / container platforms, GPU infrastructure, data/analytics (e.g. Databricks-style patterns on Azure), and core Azure storage/networking dependencies. Align ANF's AI story with Azure-wide AI data guidance and reference architectures, and feed real customer workload evidence back into joint planning. Cross-functional leadership Lead across engineering, product marketing, sales, customer success, and professional services to ship capabilities and repeatable reference architectures / proof points. Engage strategic customers and design partners to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into differentiated bets. Represent ANF as a credible technical executive in briefings, advisory councils, and industry forums. Industry segmentation Tailor AI storage strategy for segments where file semantics and performance matter, for example: semiconductor/EDA, manufacturing, healthcare imaging, financial services, energy, media & entertainment, and HPC/simulation-including compliance and data residency realities. AI strategy & roadmap Own end-to-end AI strategy for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. Prioritize investments across performance, scale, data services, protocol and API surfaces, and operational excellence for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) RAG and enterprise search (datasets, versioning, clones, refresh patterns) Agentic workflows and orchestration (durable shared state, tool/data access patterns-where productized responsibly) Large multimodal and enterprise datasets (governance, access control, lifecycle) Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership Partner with Microsoft teams across Azure AI / Foundry, Azure Machine Learning, AKS / container platforms, GPU infrastructure, data/analytics (e.g. Databricks-style patterns on Azure), and core Azure storage/networking dependencies. Align ANF's AI story with Azure-wide AI data guidance and reference architectures, and feed real customer workload evidence back into joint planning. Cross-functional leadership Lead across engineering, product marketing, sales, customer success, and professional services to ship capabilities and repeatable reference architectures / proof points. Engage strategic customers and design partners to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into differentiated bets. Represent ANF as a credible technical executive in briefings, advisory councils, and industry forums. Industry segmentation Tailor AI storage strategy for segments where file semantics and performance matter, for example: semiconductor/EDA, manufacturing, healthcare imaging, financial services, energy, media & entertainment, and HPC/simulation-including compliance and data residency realities. Job Requirements Required 10+ years product management in cloud infrastructure, enterprise storage, AI/ML infrastructure, or data platforms (principal scope: portfolio strategy, multi-team alignment, executive storytelling). Strong command of enterprise storage: NFS/SMB semantics, snapshots/clones, replication, backup integration patterns, capacity/performance tiers, and large-scale filesystem behavior under parallel workloads. Hands-on familiarity with modern AI stacks: LLMs, RAG architectures, embeddings/vector retrieval patterns, training vs. inference IO profiles, orchestration, and enterprise AI data pipelines. Demonstrated success influencing engineering and partner roadmaps without direct authority; experience with hyperscaler first-party or deeply partnered services is a strong plus. Excellent written and verbal communication to customers, executives, and engineers. Preferred Direct experience with Microsoft Azure AI services, GPU estates on Azure, and/or Azure Kubernetes Service + ML platform integrations. Familiarity with Databricks, Iceberg/Delta-class open table patterns, Kubernetes storage patterns, NVIDIA AI software stacks, and enterprise MLOps release cadences. Background in regulated industries and enterprise security/governance requirements for AI data. Education MBA or advanced degree in CS/Engineering (helpful, not a substitute for demonstrated technical depth). Compensation: The target salary range for this position is $228,000 - $325,000. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off, various Leave options, Performance-Based Incentives, employee stock purchase plan, and/or restricted stocks (RSU's), with all offerings subject to regional variations and governed by local laws, regulations, and company policies. Benefits may vary by country and region, and further details will be provided as part of the recruitment process. At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in-office and/or in-person expectations, which will be shared during the recruitment process. Equal Opportunity Employer: NetApp is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all federal . click apply for full job details
Own Every Moment at NetApp While professional experience and qualifications are key for this role, make sure to check you have the preferable soft skills before applying if required. At NetApp, your ideas power innovation. We lead in intelligent data infrastructure-delivering unified storage, integrated data services, and solutions that help organizations unlock the full potential of their data, from AI to multicloud. Ready to innovate and contribute to our path to $10B? Here, you'll collaborate with passionate teams, tackle real-world challenges, and see your impact in how customers transform and grow. If you're ready to bring curiosity, creativity, and drive to every moment, NetApp is where your journey begins. Job Summary NetApp is hiring a?principal-level product leader?to own the?AI product strategy?for?Azure NetApp Files (ANF)-a?first-party, fully managed enterprise file service on Microsoft Azure, delivered in deep partnership between NetApp and Microsoft. In the spirit of NetApp's?"business builder"?cloud roles, you will translate a fast-moving AI landscape into?differentiated platform capabilities,?joint roadmap bets?with Microsoft, and?enterprise outcomes?(performance, data locality, governance, and time-to-value for AI pipelines). You will sit at the intersection of?enterprise storage,?Azure AI infrastructure, and?industry AI workloads, ensuring ANF is positioned and built as a?strategic data foundation?for training, inference, RAG, analytics, simulation, and agentic workflows-without forcing customers to abandon enterprise file semantics, protection, or hybrid operating models. Role Overview We need a?highly strategic and deeply technical?principal PM who can: Define?multi-year AI vision and roadmap?for ANF in the context of Azure AI services, GPU estates, data platforms, and regulated enterprise environments. Turn emerging patterns (LLMs, RAG, agents, orchestration, multimodal data, vector retrieval, high-throughput checkpointing) into?concrete product requirements?and?joint go-to-market?narratives with Microsoft. Balance?hyperscaler co-development?constraints with?NetApp differentiation?(enterprise data services, multiprotocol access, lifecycle management, resiliency, and cross-cloud consistency where relevant). Responsibilities AI strategy & roadmap Own end-to-end?AI strategy?for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. Prioritize investments across?performance,?scale,?data services,?protocol and API surfaces, and?operational excellence?for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) RAG and enterprise search (datasets, versioning, clones, refresh patterns) Agentic workflows and orchestration (durable shared state, tool/data access patterns-where productized responsibly) Large multimodal and enterprise datasets (governance, access control, lifecycle) Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership Partner with?Microsoft?teams across?Azure AI / Foundry,?Azure Machine Learning,?AKS / container platforms,?GPU infrastructure,?data/analytics?(e.g. Databricks-style patterns on Azure), and core Azure storage/networking dependencies. Align ANF's AI story with?Azure-wide AI data?guidance and reference architectures, and feed?real customer workload evidence?back into joint planning. Cross-functional leadership Lead across?engineering, product marketing, sales, customer success, and professional services?to ship capabilities and repeatable?reference architectures / proof points. Engage?strategic customers?and?design partners?to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into?differentiated bets. Represent ANF as a?credible technical executive?in briefings, advisory councils, and industry forums. Industry segmentation Tailor AI storage strategy for segments where file semantics and performance matter, for example:?semiconductor/EDA,?manufacturing,?healthcare imaging,?financial services,?energy,?media & entertainment, and?HPC/simulation-including compliance and data residency realities. AI strategy & roadmap Own end-to-end?AI strategy?for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. Prioritize investments across?performance,?scale,?data services,?protocol and API surfaces, and?operational excellence?for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) RAG and enterprise search (datasets, versioning, clones, refresh patterns) Agentic workflows and orchestration (durable shared state, tool/data access patterns-where productized responsibly) Large multimodal and enterprise datasets (governance, access control, lifecycle) Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership Partner with?Microsoft?teams across?Azure AI / Foundry,?Azure Machine Learning,?AKS / container platforms,?GPU infrastructure,?data/analytics?(e.g. Databricks-style patterns on Azure), and core Azure storage/networking dependencies. Align ANF's AI story with?Azure-wide AI data?guidance and reference architectures, and feed?real customer workload evidence?back into joint planning. Cross-functional leadership Lead across?engineering, product marketing, sales, customer success, and professional services?to ship capabilities and repeatable?reference architectures / proof points. Engage?strategic customers?and?design partners?to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into?differentiated bets. Represent ANF as a?credible technical executive?in briefings, advisory councils, and industry forums. Industry segmentation Tailor AI storage strategy for segments where file semantics and performance matter, for example:?semiconductor/EDA,?manufacturing,?healthcare imaging,?financial services,?energy,?media & entertainment, and?HPC/simulation-including compliance and data residency realities. Job Requirements Required 10+ years?product management in?cloud infrastructure,?enterprise storage,?AI/ML infrastructure, or?data platforms?(principal scope: portfolio strategy, multi-team alignment, executive storytelling). Strong command of?enterprise storage: NFS/SMB semantics, snapshots/clones, replication, backup integration patterns, capacity/performance tiers, and large-scale filesystem behavior under parallel workloads. Hands-on familiarity with?modern AI stacks: LLMs, RAG architectures, embeddings/vector retrieval patterns, training vs. inference IO profiles, orchestration, and enterprise AI data pipelines. Demonstrated success influencing?engineering and partner roadmaps?without direct authority; experience with?hyperscaler first-party?or deeply partnered services is a strong plus. Excellent written and verbal communication to?customers, executives, and engineers. Preferred Direct experience with?Microsoft Azure?AI services,?GPU?estates on Azure, and/or?Azure Kubernetes Service?+ ML platform integrations. Familiarity with?Databricks,?Iceberg/Delta-class open table patterns,?Kubernetes?storage patterns,?NVIDIA AI?software stacks, and?enterprise MLOps?release cadences. Background in?regulated industries?and enterprise security/governance requirements for AI data. Education MBA?or advanced degree in?CS/Engineering?(helpful, not a substitute for demonstrated technical depth). Compensation: The target salary range for this position is $228,000 - $325,000. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off, various Leave options, Performance-Based Incentives, employee stock purchase plan, and/or restricted stocks (RSU's), with all offerings subject to regional variations and governed by local laws, regulations, and company policies. Benefits may vary by country and region, and further details will be provided as part of the recruitment process. At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in-office and/or in-person expectations, which will be shared during the recruitment process. Equal Opportunity Employer: . click apply for full job details
06/08/2026
Full time
Own Every Moment at NetApp While professional experience and qualifications are key for this role, make sure to check you have the preferable soft skills before applying if required. At NetApp, your ideas power innovation. We lead in intelligent data infrastructure-delivering unified storage, integrated data services, and solutions that help organizations unlock the full potential of their data, from AI to multicloud. Ready to innovate and contribute to our path to $10B? Here, you'll collaborate with passionate teams, tackle real-world challenges, and see your impact in how customers transform and grow. If you're ready to bring curiosity, creativity, and drive to every moment, NetApp is where your journey begins. Job Summary NetApp is hiring a?principal-level product leader?to own the?AI product strategy?for?Azure NetApp Files (ANF)-a?first-party, fully managed enterprise file service on Microsoft Azure, delivered in deep partnership between NetApp and Microsoft. In the spirit of NetApp's?"business builder"?cloud roles, you will translate a fast-moving AI landscape into?differentiated platform capabilities,?joint roadmap bets?with Microsoft, and?enterprise outcomes?(performance, data locality, governance, and time-to-value for AI pipelines). You will sit at the intersection of?enterprise storage,?Azure AI infrastructure, and?industry AI workloads, ensuring ANF is positioned and built as a?strategic data foundation?for training, inference, RAG, analytics, simulation, and agentic workflows-without forcing customers to abandon enterprise file semantics, protection, or hybrid operating models. Role Overview We need a?highly strategic and deeply technical?principal PM who can: Define?multi-year AI vision and roadmap?for ANF in the context of Azure AI services, GPU estates, data platforms, and regulated enterprise environments. Turn emerging patterns (LLMs, RAG, agents, orchestration, multimodal data, vector retrieval, high-throughput checkpointing) into?concrete product requirements?and?joint go-to-market?narratives with Microsoft. Balance?hyperscaler co-development?constraints with?NetApp differentiation?(enterprise data services, multiprotocol access, lifecycle management, resiliency, and cross-cloud consistency where relevant). Responsibilities AI strategy & roadmap Own end-to-end?AI strategy?for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. Prioritize investments across?performance,?scale,?data services,?protocol and API surfaces, and?operational excellence?for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) RAG and enterprise search (datasets, versioning, clones, refresh patterns) Agentic workflows and orchestration (durable shared state, tool/data access patterns-where productized responsibly) Large multimodal and enterprise datasets (governance, access control, lifecycle) Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership Partner with?Microsoft?teams across?Azure AI / Foundry,?Azure Machine Learning,?AKS / container platforms,?GPU infrastructure,?data/analytics?(e.g. Databricks-style patterns on Azure), and core Azure storage/networking dependencies. Align ANF's AI story with?Azure-wide AI data?guidance and reference architectures, and feed?real customer workload evidence?back into joint planning. Cross-functional leadership Lead across?engineering, product marketing, sales, customer success, and professional services?to ship capabilities and repeatable?reference architectures / proof points. Engage?strategic customers?and?design partners?to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into?differentiated bets. Represent ANF as a?credible technical executive?in briefings, advisory councils, and industry forums. Industry segmentation Tailor AI storage strategy for segments where file semantics and performance matter, for example:?semiconductor/EDA,?manufacturing,?healthcare imaging,?financial services,?energy,?media & entertainment, and?HPC/simulation-including compliance and data residency realities. AI strategy & roadmap Own end-to-end?AI strategy?for ANF: problem selection, success metrics, phased delivery, and competitive positioning vs. other Azure and AI-native storage options. Prioritize investments across?performance,?scale,?data services,?protocol and API surfaces, and?operational excellence?for AI pipelines. Workload-led product definition Drive requirements for AI-centric scenarios, including: Training and inference data planes (high throughput, low latency, checkpointing, bursty I/O) RAG and enterprise search (datasets, versioning, clones, refresh patterns) Agentic workflows and orchestration (durable shared state, tool/data access patterns-where productized responsibly) Large multimodal and enterprise datasets (governance, access control, lifecycle) Analytics and simulation adjacencies (HPC/EDA-style throughput, shared filesystem semantics) Hyperscaler & ecosystem partnership Partner with?Microsoft?teams across?Azure AI / Foundry,?Azure Machine Learning,?AKS / container platforms,?GPU infrastructure,?data/analytics?(e.g. Databricks-style patterns on Azure), and core Azure storage/networking dependencies. Align ANF's AI story with?Azure-wide AI data?guidance and reference architectures, and feed?real customer workload evidence?back into joint planning. Cross-functional leadership Lead across?engineering, product marketing, sales, customer success, and professional services?to ship capabilities and repeatable?reference architectures / proof points. Engage?strategic customers?and?design partners?to validate pain, quantify value, and de-risk roadmap bets. Market intelligence & evangelism Monitor AI infrastructure trends (models, frameworks, orchestration, data formats) and competitor moves; translate into?differentiated bets. Represent ANF as a?credible technical executive?in briefings, advisory councils, and industry forums. Industry segmentation Tailor AI storage strategy for segments where file semantics and performance matter, for example:?semiconductor/EDA,?manufacturing,?healthcare imaging,?financial services,?energy,?media & entertainment, and?HPC/simulation-including compliance and data residency realities. Job Requirements Required 10+ years?product management in?cloud infrastructure,?enterprise storage,?AI/ML infrastructure, or?data platforms?(principal scope: portfolio strategy, multi-team alignment, executive storytelling). Strong command of?enterprise storage: NFS/SMB semantics, snapshots/clones, replication, backup integration patterns, capacity/performance tiers, and large-scale filesystem behavior under parallel workloads. Hands-on familiarity with?modern AI stacks: LLMs, RAG architectures, embeddings/vector retrieval patterns, training vs. inference IO profiles, orchestration, and enterprise AI data pipelines. Demonstrated success influencing?engineering and partner roadmaps?without direct authority; experience with?hyperscaler first-party?or deeply partnered services is a strong plus. Excellent written and verbal communication to?customers, executives, and engineers. Preferred Direct experience with?Microsoft Azure?AI services,?GPU?estates on Azure, and/or?Azure Kubernetes Service?+ ML platform integrations. Familiarity with?Databricks,?Iceberg/Delta-class open table patterns,?Kubernetes?storage patterns,?NVIDIA AI?software stacks, and?enterprise MLOps?release cadences. Background in?regulated industries?and enterprise security/governance requirements for AI data. Education MBA?or advanced degree in?CS/Engineering?(helpful, not a substitute for demonstrated technical depth). Compensation: The target salary range for this position is $228,000 - $325,000. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off, various Leave options, Performance-Based Incentives, employee stock purchase plan, and/or restricted stocks (RSU's), with all offerings subject to regional variations and governed by local laws, regulations, and company policies. Benefits may vary by country and region, and further details will be provided as part of the recruitment process. At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in-office and/or in-person expectations, which will be shared during the recruitment process. Equal Opportunity Employer: . click apply for full job details
It's an exciting time to join Fisher Investments; we're investing in the future of our firm's technology and information security. Our business is growing internationally, which emphasizes the need to build an unparalleled team that promotes future global growth through strategic solutions and progress. We are important to supporting our firm's diverse businesses, and we're excited to continue solidifying that foundation as we add more experienced technologists to our Technology team. -We are looking for a Sr. Platform Engineer to design and develop solutions for enterprise data warehouses/data marts and analytics as part of a collection of systems in a large technology ecosystem. You will report to the Application Development Team Leader. -The Opportunity: -As a Sr. Platform Engineer, you will perform design and administration of our Azure data and analytics platform to ensure smooth system operations and be the guide for architectural principles and standards. As a technical expert for our data and analytics ecosystem, you will support Fisher Investments business line reporting teams and Technology Business data delivery teams. This hands-on role will provide direction to other developers of data warehouse workloads and data related projects. -You will help align department-wide solutions to Fisher's enterprise priorities and survey the technology landscape and guide the evolution of current environment to support future capabilities and requirements. You will be a part of the team that plans the technology to ensure capacity and scalability as demand and usage evolves. -The Day-to-Day: Work with business and technology partners to analyze how the data warehouse, analytics and application will meet our goals Evaluate all proposed requests to determine fit with data warehouse, analytics and application solution architecture. Own data warehouse and analytics technical platform on Azure, from implementation to enhancements and ongoing operations Design, develop and coordinate cloud data and application solutions/projects across diverse groups and areas including enterprise architecture, application development, identity and access management, network and data management Provide technical direction and guidance to database and application developers Develop cloud security and access control solution/policy, data and BI standards, guidelines and best practice for business groups and technical teams Perform maintenance and troubleshooting activities for data warehouse, BI platform and other data projects and resolve issues Monitor system application logs and identify potential issues and improvements to ensure smooth operations Perform capacity planning, cloud cost analysis and optimization and provide recommendations to management Provide after-hour system and application support Develop multiple work plans for projects and prepare appropriate status reports and submit them to managementYour Qualifications: Minimum of 8 years of experience developing software and data solution for enterprise environment focusing on data and cloud applications with direct experience with application development, data warehouse and BI design, implementation, and operation Experience with cloud data warehouse and analytics technologies, specifically Azure Databricks, Azure Synapse, Azure Data Factory, Azure Data Lake Storage, Power BI, and other Azure data solutions Knowledge or experience with infrastructure (operating system and networking) and cloud administration and automation such as Terraform for Infrastructure as Code. Knowledge of DevOps in application development such as GitHub Actions, or Powershell Experience with application development using Microsoft or cloud technologies (such as SQL, Azure, C#, Python) Experience with Machine Learning, MLOps Experience with investment management systems and processes Experience with Agile methodologies in a cloud, application, database, data warehousing and BI space BS or equivalent in Computer Science or related field or a combination of technical skills, cloud, operating system, networking, security, data application, data modeling and BI backgroundCompensation: $120,000 - $165,000 base salary per year in the state of WA. New hires should expect to start at the lower end of the range depending on experience Eligible for a discretionary bonus based on firm and individual performanceWhy Fisher Investments: -We work for a bigger purpose: bettering the investment universe. We take great pride in our inclusive culture, our learning and development framework customized for every employee, and our Great Place to Work Certification. It's the people that make the Fisher purpose possible, and we invest in them by offering exceptional benefits like: 100% paid medical, dental and vision premiums for you and your qualifying dependents A 50% 401(k) match, up to the IRS maximum 20 days of PTO, plus 10 paid holidays Family Support programs including 8 week Paid Primary Caregiver Leave, $10,000 fertility, family forming, and hormonal health assistance, and back-up child, adult, and elder care This is an in-office role. Based on your role, tenure, and performance eligibility you may have the opportunity to participate in our hybrid work from home program. This program is subject to change. FISHER INVESTMENTS IS AN EQUAL OPPORTUNITY EMPLOYER
06/08/2026
It's an exciting time to join Fisher Investments; we're investing in the future of our firm's technology and information security. Our business is growing internationally, which emphasizes the need to build an unparalleled team that promotes future global growth through strategic solutions and progress. We are important to supporting our firm's diverse businesses, and we're excited to continue solidifying that foundation as we add more experienced technologists to our Technology team. -We are looking for a Sr. Platform Engineer to design and develop solutions for enterprise data warehouses/data marts and analytics as part of a collection of systems in a large technology ecosystem. You will report to the Application Development Team Leader. -The Opportunity: -As a Sr. Platform Engineer, you will perform design and administration of our Azure data and analytics platform to ensure smooth system operations and be the guide for architectural principles and standards. As a technical expert for our data and analytics ecosystem, you will support Fisher Investments business line reporting teams and Technology Business data delivery teams. This hands-on role will provide direction to other developers of data warehouse workloads and data related projects. -You will help align department-wide solutions to Fisher's enterprise priorities and survey the technology landscape and guide the evolution of current environment to support future capabilities and requirements. You will be a part of the team that plans the technology to ensure capacity and scalability as demand and usage evolves. -The Day-to-Day: Work with business and technology partners to analyze how the data warehouse, analytics and application will meet our goals Evaluate all proposed requests to determine fit with data warehouse, analytics and application solution architecture. Own data warehouse and analytics technical platform on Azure, from implementation to enhancements and ongoing operations Design, develop and coordinate cloud data and application solutions/projects across diverse groups and areas including enterprise architecture, application development, identity and access management, network and data management Provide technical direction and guidance to database and application developers Develop cloud security and access control solution/policy, data and BI standards, guidelines and best practice for business groups and technical teams Perform maintenance and troubleshooting activities for data warehouse, BI platform and other data projects and resolve issues Monitor system application logs and identify potential issues and improvements to ensure smooth operations Perform capacity planning, cloud cost analysis and optimization and provide recommendations to management Provide after-hour system and application support Develop multiple work plans for projects and prepare appropriate status reports and submit them to managementYour Qualifications: Minimum of 8 years of experience developing software and data solution for enterprise environment focusing on data and cloud applications with direct experience with application development, data warehouse and BI design, implementation, and operation Experience with cloud data warehouse and analytics technologies, specifically Azure Databricks, Azure Synapse, Azure Data Factory, Azure Data Lake Storage, Power BI, and other Azure data solutions Knowledge or experience with infrastructure (operating system and networking) and cloud administration and automation such as Terraform for Infrastructure as Code. Knowledge of DevOps in application development such as GitHub Actions, or Powershell Experience with application development using Microsoft or cloud technologies (such as SQL, Azure, C#, Python) Experience with Machine Learning, MLOps Experience with investment management systems and processes Experience with Agile methodologies in a cloud, application, database, data warehousing and BI space BS or equivalent in Computer Science or related field or a combination of technical skills, cloud, operating system, networking, security, data application, data modeling and BI backgroundCompensation: $120,000 - $165,000 base salary per year in the state of WA. New hires should expect to start at the lower end of the range depending on experience Eligible for a discretionary bonus based on firm and individual performanceWhy Fisher Investments: -We work for a bigger purpose: bettering the investment universe. We take great pride in our inclusive culture, our learning and development framework customized for every employee, and our Great Place to Work Certification. It's the people that make the Fisher purpose possible, and we invest in them by offering exceptional benefits like: 100% paid medical, dental and vision premiums for you and your qualifying dependents A 50% 401(k) match, up to the IRS maximum 20 days of PTO, plus 10 paid holidays Family Support programs including 8 week Paid Primary Caregiver Leave, $10,000 fertility, family forming, and hormonal health assistance, and back-up child, adult, and elder care This is an in-office role. Based on your role, tenure, and performance eligibility you may have the opportunity to participate in our hybrid work from home program. This program is subject to change. FISHER INVESTMENTS IS AN EQUAL OPPORTUNITY EMPLOYER
It's an exciting time to join Fisher Investments; we're investing in the future of our firm's technology and information security. Our business is growing internationally, which emphasizes the need to build an unparalleled team that promotes future global growth through strategic solutions and progress. We are important to supporting our firm's diverse businesses, and we're excited to continue solidifying that foundation as we add more experienced technologists to our Technology team. -We are looking for a Sr. Platform Engineer to design and develop solutions for enterprise data warehouses/data marts and analytics as part of a collection of systems in a large technology ecosystem. You will report to the Application Development Team Leader. -The Opportunity: -As a Sr. Platform Engineer, you will perform design and administration of our Azure data and analytics platform to ensure smooth system operations and be the guide for architectural principles and standards. As a technical expert for our data and analytics ecosystem, you will support Fisher Investments business line reporting teams and Technology Business data delivery teams. This hands-on role will provide direction to other developers of data warehouse workloads and data related projects. -You will help align department-wide solutions to Fisher's enterprise priorities and survey the technology landscape and guide the evolution of current environment to support future capabilities and requirements. You will be a part of the team that plans the technology to ensure capacity and scalability as demand and usage evolves. -The Day-to-Day: Work with business and technology partners to analyze how the data warehouse, analytics and application will meet our goals Evaluate all proposed requests to determine fit with data warehouse, analytics and application solution architecture. Own data warehouse and analytics technical platform on Azure, from implementation to enhancements and ongoing operations Design, develop and coordinate cloud data and application solutions/projects across diverse groups and areas including enterprise architecture, application development, identity and access management, network and data management Provide technical direction and guidance to database and application developers Develop cloud security and access control solution/policy, data and BI standards, guidelines and best practice for business groups and technical teams Perform maintenance and troubleshooting activities for data warehouse, BI platform and other data projects and resolve issues Monitor system application logs and identify potential issues and improvements to ensure smooth operations Perform capacity planning, cloud cost analysis and optimization and provide recommendations to management Provide after-hour system and application support Develop multiple work plans for projects and prepare appropriate status reports and submit them to managementYour Qualifications: Minimum of 8 years of experience developing software and data solution for enterprise environment focusing on data and cloud applications with direct experience with application development, data warehouse and BI design, implementation, and operation Experience with cloud data warehouse and analytics technologies, specifically Azure Databricks, Azure Synapse, Azure Data Factory, Azure Data Lake Storage, Power BI, and other Azure data solutions Knowledge or experience with infrastructure (operating system and networking) and cloud administration and automation such as Terraform for Infrastructure as Code. Knowledge of DevOps in application development such as GitHub Actions, or Powershell Experience with application development using Microsoft or cloud technologies (such as SQL, Azure, C#, Python) Experience with Machine Learning, MLOps Experience with investment management systems and processes Experience with Agile methodologies in a cloud, application, database, data warehousing and BI space BS or equivalent in Computer Science or related field or a combination of technical skills, cloud, operating system, networking, security, data application, data modeling and BI backgroundWhy Fisher Investments: -We work for a bigger purpose: bettering the investment universe. We take great pride in our inclusive culture, our learning and development framework customized for every employee, and our Great Place to Work Certification. It's the people that make the Fisher purpose possible, and we invest in them by offering exceptional benefits like: 100% paid medical, dental and vision premiums for you and your qualifying dependents A 50% 401(k) match, up to the IRS maximum 20 days of PTO, plus 10 paid holidays Family Support programs including 8 week Paid Primary Caregiver Leave, $10,000 fertility, family forming, and hormonal health assistance, and back-up child, adult, and elder care This is an in-office role. Based on your role, tenure, and performance eligibility you may have the opportunity to participate in our hybrid work from home program. This program is subject to change. FISHER INVESTMENTS IS AN EQUAL OPPORTUNITY EMPLOYER
06/08/2026
It's an exciting time to join Fisher Investments; we're investing in the future of our firm's technology and information security. Our business is growing internationally, which emphasizes the need to build an unparalleled team that promotes future global growth through strategic solutions and progress. We are important to supporting our firm's diverse businesses, and we're excited to continue solidifying that foundation as we add more experienced technologists to our Technology team. -We are looking for a Sr. Platform Engineer to design and develop solutions for enterprise data warehouses/data marts and analytics as part of a collection of systems in a large technology ecosystem. You will report to the Application Development Team Leader. -The Opportunity: -As a Sr. Platform Engineer, you will perform design and administration of our Azure data and analytics platform to ensure smooth system operations and be the guide for architectural principles and standards. As a technical expert for our data and analytics ecosystem, you will support Fisher Investments business line reporting teams and Technology Business data delivery teams. This hands-on role will provide direction to other developers of data warehouse workloads and data related projects. -You will help align department-wide solutions to Fisher's enterprise priorities and survey the technology landscape and guide the evolution of current environment to support future capabilities and requirements. You will be a part of the team that plans the technology to ensure capacity and scalability as demand and usage evolves. -The Day-to-Day: Work with business and technology partners to analyze how the data warehouse, analytics and application will meet our goals Evaluate all proposed requests to determine fit with data warehouse, analytics and application solution architecture. Own data warehouse and analytics technical platform on Azure, from implementation to enhancements and ongoing operations Design, develop and coordinate cloud data and application solutions/projects across diverse groups and areas including enterprise architecture, application development, identity and access management, network and data management Provide technical direction and guidance to database and application developers Develop cloud security and access control solution/policy, data and BI standards, guidelines and best practice for business groups and technical teams Perform maintenance and troubleshooting activities for data warehouse, BI platform and other data projects and resolve issues Monitor system application logs and identify potential issues and improvements to ensure smooth operations Perform capacity planning, cloud cost analysis and optimization and provide recommendations to management Provide after-hour system and application support Develop multiple work plans for projects and prepare appropriate status reports and submit them to managementYour Qualifications: Minimum of 8 years of experience developing software and data solution for enterprise environment focusing on data and cloud applications with direct experience with application development, data warehouse and BI design, implementation, and operation Experience with cloud data warehouse and analytics technologies, specifically Azure Databricks, Azure Synapse, Azure Data Factory, Azure Data Lake Storage, Power BI, and other Azure data solutions Knowledge or experience with infrastructure (operating system and networking) and cloud administration and automation such as Terraform for Infrastructure as Code. Knowledge of DevOps in application development such as GitHub Actions, or Powershell Experience with application development using Microsoft or cloud technologies (such as SQL, Azure, C#, Python) Experience with Machine Learning, MLOps Experience with investment management systems and processes Experience with Agile methodologies in a cloud, application, database, data warehousing and BI space BS or equivalent in Computer Science or related field or a combination of technical skills, cloud, operating system, networking, security, data application, data modeling and BI backgroundWhy Fisher Investments: -We work for a bigger purpose: bettering the investment universe. We take great pride in our inclusive culture, our learning and development framework customized for every employee, and our Great Place to Work Certification. It's the people that make the Fisher purpose possible, and we invest in them by offering exceptional benefits like: 100% paid medical, dental and vision premiums for you and your qualifying dependents A 50% 401(k) match, up to the IRS maximum 20 days of PTO, plus 10 paid holidays Family Support programs including 8 week Paid Primary Caregiver Leave, $10,000 fertility, family forming, and hormonal health assistance, and back-up child, adult, and elder care This is an in-office role. Based on your role, tenure, and performance eligibility you may have the opportunity to participate in our hybrid work from home program. This program is subject to change. FISHER INVESTMENTS IS AN EQUAL OPPORTUNITY EMPLOYER
It's an exciting time to join Fisher Investments; we're investing in the future of our firm's technology and information security. Our business is growing internationally, which emphasizes the need to build an unparalleled team that promotes future global growth through strategic solutions and progress. We are important to supporting our firm's diverse businesses, and we're excited to continue solidifying that foundation as we add more experienced technologists to our Technology team. -We are looking for a Sr. Platform Engineer to design and develop solutions for enterprise data warehouses/data marts and analytics as part of a collection of systems in a large technology ecosystem. You will report to the Application Development Team Leader. -The Opportunity: -As a Sr. Platform Engineer, you will perform design and administration of our Azure data and analytics platform to ensure smooth system operations and be the guide for architectural principles and standards. As a technical expert for our data and analytics ecosystem, you will support Fisher Investments business line reporting teams and Technology Business data delivery teams. This hands-on role will provide direction to other developers of data warehouse workloads and data related projects. -You will help align department-wide solutions to Fisher's enterprise priorities and survey the technology landscape and guide the evolution of current environment to support future capabilities and requirements. You will be a part of the team that plans the technology to ensure capacity and scalability as demand and usage evolves. -The Day-to-Day: Work with business and technology partners to analyze how the data warehouse, analytics and application will meet our goals Evaluate all proposed requests to determine fit with data warehouse, analytics and application solution architecture. Own data warehouse and analytics technical platform on Azure, from implementation to enhancements and ongoing operations Design, develop and coordinate cloud data and application solutions/projects across diverse groups and areas including enterprise architecture, application development, identity and access management, network and data management Provide technical direction and guidance to database and application developers Develop cloud security and access control solution/policy, data and BI standards, guidelines and best practice for business groups and technical teams Perform maintenance and troubleshooting activities for data warehouse, BI platform and other data projects and resolve issues Monitor system application logs and identify potential issues and improvements to ensure smooth operations Perform capacity planning, cloud cost analysis and optimization and provide recommendations to management Provide after-hour system and application support Develop multiple work plans for projects and prepare appropriate status reports and submit them to managementYour Qualifications: Minimum of 8 years of experience developing software and data solution for enterprise environment focusing on data and cloud applications with direct experience with application development, data warehouse and BI design, implementation, and operation Experience with cloud data warehouse and analytics technologies, specifically Azure Databricks, Azure Synapse, Azure Data Factory, Azure Data Lake Storage, Power BI, and other Azure data solutions Knowledge or experience with infrastructure (operating system and networking) and cloud administration and automation such as Terraform for Infrastructure as Code. Knowledge of DevOps in application development such as GitHub Actions, or Powershell Experience with application development using Microsoft or cloud technologies (such as SQL, Azure, C#, Python) Experience with Machine Learning, MLOps Experience with investment management systems and processes Experience with Agile methodologies in a cloud, application, database, data warehousing and BI space BS or equivalent in Computer Science or related field or a combination of technical skills, cloud, operating system, networking, security, data application, data modeling and BI backgroundWhy Fisher Investments: -We work for a bigger purpose: bettering the investment universe. We take great pride in our inclusive culture, our learning and development framework customized for every employee, and our Great Place to Work Certification. It's the people that make the Fisher purpose possible, and we invest in them by offering exceptional benefits like: 100% paid medical, dental and vision premiums for you and your qualifying dependents A 50% 401(k) match, up to the IRS maximum 20 days of PTO, plus 10 paid holidays Family Support programs including 8 week Paid Primary Caregiver Leave, $10,000 fertility, family forming, and hormonal health assistance, and back-up child, adult, and elder care This is an in-office role. Based on your role, tenure, and performance eligibility you may have the opportunity to participate in our hybrid work from home program. This program is subject to change. FISHER INVESTMENTS IS AN EQUAL OPPORTUNITY EMPLOYER
06/08/2026
It's an exciting time to join Fisher Investments; we're investing in the future of our firm's technology and information security. Our business is growing internationally, which emphasizes the need to build an unparalleled team that promotes future global growth through strategic solutions and progress. We are important to supporting our firm's diverse businesses, and we're excited to continue solidifying that foundation as we add more experienced technologists to our Technology team. -We are looking for a Sr. Platform Engineer to design and develop solutions for enterprise data warehouses/data marts and analytics as part of a collection of systems in a large technology ecosystem. You will report to the Application Development Team Leader. -The Opportunity: -As a Sr. Platform Engineer, you will perform design and administration of our Azure data and analytics platform to ensure smooth system operations and be the guide for architectural principles and standards. As a technical expert for our data and analytics ecosystem, you will support Fisher Investments business line reporting teams and Technology Business data delivery teams. This hands-on role will provide direction to other developers of data warehouse workloads and data related projects. -You will help align department-wide solutions to Fisher's enterprise priorities and survey the technology landscape and guide the evolution of current environment to support future capabilities and requirements. You will be a part of the team that plans the technology to ensure capacity and scalability as demand and usage evolves. -The Day-to-Day: Work with business and technology partners to analyze how the data warehouse, analytics and application will meet our goals Evaluate all proposed requests to determine fit with data warehouse, analytics and application solution architecture. Own data warehouse and analytics technical platform on Azure, from implementation to enhancements and ongoing operations Design, develop and coordinate cloud data and application solutions/projects across diverse groups and areas including enterprise architecture, application development, identity and access management, network and data management Provide technical direction and guidance to database and application developers Develop cloud security and access control solution/policy, data and BI standards, guidelines and best practice for business groups and technical teams Perform maintenance and troubleshooting activities for data warehouse, BI platform and other data projects and resolve issues Monitor system application logs and identify potential issues and improvements to ensure smooth operations Perform capacity planning, cloud cost analysis and optimization and provide recommendations to management Provide after-hour system and application support Develop multiple work plans for projects and prepare appropriate status reports and submit them to managementYour Qualifications: Minimum of 8 years of experience developing software and data solution for enterprise environment focusing on data and cloud applications with direct experience with application development, data warehouse and BI design, implementation, and operation Experience with cloud data warehouse and analytics technologies, specifically Azure Databricks, Azure Synapse, Azure Data Factory, Azure Data Lake Storage, Power BI, and other Azure data solutions Knowledge or experience with infrastructure (operating system and networking) and cloud administration and automation such as Terraform for Infrastructure as Code. Knowledge of DevOps in application development such as GitHub Actions, or Powershell Experience with application development using Microsoft or cloud technologies (such as SQL, Azure, C#, Python) Experience with Machine Learning, MLOps Experience with investment management systems and processes Experience with Agile methodologies in a cloud, application, database, data warehousing and BI space BS or equivalent in Computer Science or related field or a combination of technical skills, cloud, operating system, networking, security, data application, data modeling and BI backgroundWhy Fisher Investments: -We work for a bigger purpose: bettering the investment universe. We take great pride in our inclusive culture, our learning and development framework customized for every employee, and our Great Place to Work Certification. It's the people that make the Fisher purpose possible, and we invest in them by offering exceptional benefits like: 100% paid medical, dental and vision premiums for you and your qualifying dependents A 50% 401(k) match, up to the IRS maximum 20 days of PTO, plus 10 paid holidays Family Support programs including 8 week Paid Primary Caregiver Leave, $10,000 fertility, family forming, and hormonal health assistance, and back-up child, adult, and elder care This is an in-office role. Based on your role, tenure, and performance eligibility you may have the opportunity to participate in our hybrid work from home program. This program is subject to change. FISHER INVESTMENTS IS AN EQUAL OPPORTUNITY EMPLOYER
Sr. Distinguished Machine Learning Engineer (Remote-Eligible) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Consumer Engagement Platform organization at Capital One empowers rapid financial product innovation at scale and delivers developer joy, for all Capital One's consumer products and organizations, by providing well-managed, self-service, experimentation-driven, and personalized product development vehicles. Hyper Personalization org is building the intelligence and infrastructure that will enable Capital One to deliver truly individualized, real-time customer experiences at scale - turning every channel into a context-aware decisioning surface, from home feeds to marketing and servicing messages. The org's mission is to move Capital One to deliver always-on, cohort-of-one personalization, powered by resilient data foundations, production-grade ML and GenAI systems, and low-latency application platforms that make it easy for teams across the company to experiment, innovate, and serve the right experience to every customer at the right moment. What you'll do in the role: Define and drive technical strategy and roadmap for our Personalization Platform that powers real-time, personalized product experiences and multi-channel targeted user messaging across all Capital One products and services. Partner cross-functionally with Product, Data science, Cloud infrastructure, and Machine learning platform teams to align on and co-develop the advanced recommendation systems and algorithms serving our Capital One users. Develop and maintain a flexible, scalable rules engine to enable business-driven personalization logic, allowing dynamic configuration of user segmentation, targeting rules, and real-time decisioning while integrating seamlessly with ML-driven recommendations. Design, build and maintain robust ML infrastructure and pipelines to support end-to-end workflows including feature extraction, model training, testing, guardrails, model evaluation, deployment, and both real-time and batch inference - ensuring high performance, scalability, and reliability. Architect low-latency, event-driven systems for enabling real-time dynamic personalization and decisioning based on streaming data, user behavior, and contextual signals. Drive the evolution of MLOps practices by building automated metrics-backed deployment workflows, integration validation and testing systems, and scalable monitoring & observability. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Provide organizational technical leadership to influence architecture, engineering standards, cross-team strategies, mentoring engineers and driving organization wide platform innovation. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree At least 10 years of experience designing and building data-intensive solutions using distributed computing At least 7 years of experience programming in C, C++, Python, or Scala At least 4 years of experience with the full ML development lifecycle using modern technology in a business critical setting Preferred Qualifications: 8+ years of experience deploying scalable, responsible AI solutions on major cloud platforms (AWS, GCP, Azure); Master's or PhD in Computer Science or a relevant technical field. 5+ years of proven expertise in designing, implementing and scaling personalization platform and recommendation systems serving one or more areas of Feed Personalization/Ads Ranking/Targeted Marketing Messaging. 5+ years of strong proficiency in Python, Java, C++, or Golang; hands-on experience with ML frameworks (PyTorch, TensorFlow) and orchestration tools (Databricks, Airflow, Kubeflow). 5+ years of experience developing and applying state-of-the-art techniques for optimizing training and inference systems to improve hardware utilization, latency, throughput, and cost. 5+ years of deep expertise in cloud-native engineering, containerization (Docker, Kubernetes), and automated CI/CD deployment. Passion for staying on top of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Proven leadership in driving platform strategy, fostering cross-functional collaboration, and influencing technical direction across the company. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr Distinguished Machine Learning Engineer McLean, VA: $314,800 - $359,300 for Sr Distinguished Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to . click apply for full job details
06/08/2026
Full time
Sr. Distinguished Machine Learning Engineer (Remote-Eligible) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Consumer Engagement Platform organization at Capital One empowers rapid financial product innovation at scale and delivers developer joy, for all Capital One's consumer products and organizations, by providing well-managed, self-service, experimentation-driven, and personalized product development vehicles. Hyper Personalization org is building the intelligence and infrastructure that will enable Capital One to deliver truly individualized, real-time customer experiences at scale - turning every channel into a context-aware decisioning surface, from home feeds to marketing and servicing messages. The org's mission is to move Capital One to deliver always-on, cohort-of-one personalization, powered by resilient data foundations, production-grade ML and GenAI systems, and low-latency application platforms that make it easy for teams across the company to experiment, innovate, and serve the right experience to every customer at the right moment. What you'll do in the role: Define and drive technical strategy and roadmap for our Personalization Platform that powers real-time, personalized product experiences and multi-channel targeted user messaging across all Capital One products and services. Partner cross-functionally with Product, Data science, Cloud infrastructure, and Machine learning platform teams to align on and co-develop the advanced recommendation systems and algorithms serving our Capital One users. Develop and maintain a flexible, scalable rules engine to enable business-driven personalization logic, allowing dynamic configuration of user segmentation, targeting rules, and real-time decisioning while integrating seamlessly with ML-driven recommendations. Design, build and maintain robust ML infrastructure and pipelines to support end-to-end workflows including feature extraction, model training, testing, guardrails, model evaluation, deployment, and both real-time and batch inference - ensuring high performance, scalability, and reliability. Architect low-latency, event-driven systems for enabling real-time dynamic personalization and decisioning based on streaming data, user behavior, and contextual signals. Drive the evolution of MLOps practices by building automated metrics-backed deployment workflows, integration validation and testing systems, and scalable monitoring & observability. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Provide organizational technical leadership to influence architecture, engineering standards, cross-team strategies, mentoring engineers and driving organization wide platform innovation. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree At least 10 years of experience designing and building data-intensive solutions using distributed computing At least 7 years of experience programming in C, C++, Python, or Scala At least 4 years of experience with the full ML development lifecycle using modern technology in a business critical setting Preferred Qualifications: 8+ years of experience deploying scalable, responsible AI solutions on major cloud platforms (AWS, GCP, Azure); Master's or PhD in Computer Science or a relevant technical field. 5+ years of proven expertise in designing, implementing and scaling personalization platform and recommendation systems serving one or more areas of Feed Personalization/Ads Ranking/Targeted Marketing Messaging. 5+ years of strong proficiency in Python, Java, C++, or Golang; hands-on experience with ML frameworks (PyTorch, TensorFlow) and orchestration tools (Databricks, Airflow, Kubeflow). 5+ years of experience developing and applying state-of-the-art techniques for optimizing training and inference systems to improve hardware utilization, latency, throughput, and cost. 5+ years of deep expertise in cloud-native engineering, containerization (Docker, Kubernetes), and automated CI/CD deployment. Passion for staying on top of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Proven leadership in driving platform strategy, fostering cross-functional collaboration, and influencing technical direction across the company. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr Distinguished Machine Learning Engineer McLean, VA: $314,800 - $359,300 for Sr Distinguished Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to . click apply for full job details
Manager, Data Scientist - Recommendation & Personalization Systems Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives. Team Description Join an elite Applied AI team within AI Foundations, operating at the intersection of deep research and massive real-world impact. We are pioneering the next generation of personalized customer experiences across Capital One's web and mobile applications, leveraging our high-scale ML models. Our core mission involves architecting and deploying cutting-edge personalized recommendation engines. This is powered by original research into homegrown Foundation Models , advanced Reinforcement Learning techniques, and a state-of-the-art scalable architecture built for billions of interactions. Our research agenda is at the forefront of the field, actively focusing on areas such as Causal Inference , Transformer-based architectures , and sophisticated Recommender Systems . Role Description In this role, you will: Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love Leverage a broad stack of technologies - Python, Conda, AWS, H2O, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation Flex your interpersonal skills to translate the complexity of your work into tangible business goals The Ideal Candidate is: Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms. A data guru. "Big data" doesn't faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science. Basic Qualifications: Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 4 years of experience performing data analytics A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics At least 1 year of experience leveraging open source programming languages for large scale data analysis At least 1 year of experience working with machine learning At least 1 year of experience utilizing relational databases Preferred Qualifications: PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics At least 3 years of hands-on experience building, deploying, and maintaining high-scale, production-grade ML systems using MLOps practices, including AWS, Kubeflow, and CI/CD pipelines At least 4 years of experience in developing and optimizing state-of-the-art Deep Learning models, specifically Transformer-based architectures, using PyTorch and distributed training with multi-GPU optimization At least 4 years of experience with high-performance, distributed data processing for petabyte-scale feature engineering using frameworks like DASK and PySpark Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Mgr, Data Science New York, NY: $215,200 - $245,600 for Mgr, Data Science San Jose, CA: $215,200 - $245,600 for Mgr, Data Science Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
06/08/2026
Full time
Manager, Data Scientist - Recommendation & Personalization Systems Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives. Team Description Join an elite Applied AI team within AI Foundations, operating at the intersection of deep research and massive real-world impact. We are pioneering the next generation of personalized customer experiences across Capital One's web and mobile applications, leveraging our high-scale ML models. Our core mission involves architecting and deploying cutting-edge personalized recommendation engines. This is powered by original research into homegrown Foundation Models , advanced Reinforcement Learning techniques, and a state-of-the-art scalable architecture built for billions of interactions. Our research agenda is at the forefront of the field, actively focusing on areas such as Causal Inference , Transformer-based architectures , and sophisticated Recommender Systems . Role Description In this role, you will: Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love Leverage a broad stack of technologies - Python, Conda, AWS, H2O, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation Flex your interpersonal skills to translate the complexity of your work into tangible business goals The Ideal Candidate is: Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms. A data guru. "Big data" doesn't faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science. Basic Qualifications: Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 4 years of experience performing data analytics A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics At least 1 year of experience leveraging open source programming languages for large scale data analysis At least 1 year of experience working with machine learning At least 1 year of experience utilizing relational databases Preferred Qualifications: PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics At least 3 years of hands-on experience building, deploying, and maintaining high-scale, production-grade ML systems using MLOps practices, including AWS, Kubeflow, and CI/CD pipelines At least 4 years of experience in developing and optimizing state-of-the-art Deep Learning models, specifically Transformer-based architectures, using PyTorch and distributed training with multi-GPU optimization At least 4 years of experience with high-performance, distributed data processing for petabyte-scale feature engineering using frameworks like DASK and PySpark Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Mgr, Data Science New York, NY: $215,200 - $245,600 for Mgr, Data Science San Jose, CA: $215,200 - $245,600 for Mgr, Data Science Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Manager, Product Management - Enterprise AI/ML Product Management at Capital One is a booming, vibrant craft that requires reimagining the status quo, finding value creation opportunities, and driving innovative and sustainable customer experiences through technology. We believe our portfolio of businesses and investments in growth and transformation will result in a company with the scale, brand, capabilities, talent, and values to succeed as the digital revolution transforms our society and our industry. About the Team This team powers real-time, intelligent banking by safely introducing, scaling, and operationalizing new Artificial Intelligence and Machine Learning capabilities across the business. Capital One Product Framework In this role, you'll be expected to demonstrate proficiency in five key areas which we consider to be the foundation for successful Product management: Human Centered - Obsesses about internal and external customer needs to reimagine and innovate product solutions Business Focused - Delivers game-changing outcomes by focusing on leverage and execution excellence Technology Driven - Leverages technology to deliver innovative and resilient solutions that enable both near term and long term value Integrated Problem Solving - Identifies and resolves complex problems to deliver outcomes while mitigating product risks Transformational Leadership - Leads cross functional teams to solve customer problems and drive organizational alignment Basic Qualifications: At least 3 years of experience working in Product Management Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, Computer Engineering, Software Engineering, Mechanical Engineering, Information Systems or a related quantitative field) A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, Computer Engineering, Software Engineering, Mechanical Engineering, Information Systems or a related quantitative field) or an MBA with a quantitative concentration Preferred Qualifications: Experience in product management for technical platforms (data science or Machine Learning preferred), MLOps, or internal developer tools. Familiarity with cloud computing environments (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Kubernetes). Demonstrated experience working in an Agile environment and managing a product backlog. At this time, Capital One will not sponsor a new applicant for employment authorization for this position The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $164,800 - $188,100 for Manager, Product Management Chicago, IL: $149,800 - $171,000 for Manager, Product Management McLean, VA: $164,800 - $188,100 for Manager, Product Management New York, NY: $179,700 - $205,100 for Manager, Product Management Richmond, VA: $149,800 - $171,000 for Manager, Product Management San Francisco, CA: $179,700 - $205,100 for Manager, Product Management Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
06/08/2026
Full time
Manager, Product Management - Enterprise AI/ML Product Management at Capital One is a booming, vibrant craft that requires reimagining the status quo, finding value creation opportunities, and driving innovative and sustainable customer experiences through technology. We believe our portfolio of businesses and investments in growth and transformation will result in a company with the scale, brand, capabilities, talent, and values to succeed as the digital revolution transforms our society and our industry. About the Team This team powers real-time, intelligent banking by safely introducing, scaling, and operationalizing new Artificial Intelligence and Machine Learning capabilities across the business. Capital One Product Framework In this role, you'll be expected to demonstrate proficiency in five key areas which we consider to be the foundation for successful Product management: Human Centered - Obsesses about internal and external customer needs to reimagine and innovate product solutions Business Focused - Delivers game-changing outcomes by focusing on leverage and execution excellence Technology Driven - Leverages technology to deliver innovative and resilient solutions that enable both near term and long term value Integrated Problem Solving - Identifies and resolves complex problems to deliver outcomes while mitigating product risks Transformational Leadership - Leads cross functional teams to solve customer problems and drive organizational alignment Basic Qualifications: At least 3 years of experience working in Product Management Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, Computer Engineering, Software Engineering, Mechanical Engineering, Information Systems or a related quantitative field) A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, Computer Engineering, Software Engineering, Mechanical Engineering, Information Systems or a related quantitative field) or an MBA with a quantitative concentration Preferred Qualifications: Experience in product management for technical platforms (data science or Machine Learning preferred), MLOps, or internal developer tools. Familiarity with cloud computing environments (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Kubernetes). Demonstrated experience working in an Agile environment and managing a product backlog. At this time, Capital One will not sponsor a new applicant for employment authorization for this position The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $164,800 - $188,100 for Manager, Product Management Chicago, IL: $149,800 - $171,000 for Manager, Product Management McLean, VA: $164,800 - $188,100 for Manager, Product Management New York, NY: $179,700 - $205,100 for Manager, Product Management Richmond, VA: $149,800 - $171,000 for Manager, Product Management San Francisco, CA: $179,700 - $205,100 for Manager, Product Management Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Manager, Product Management - Enterprise AI/ML Product Management at Capital One is a booming, vibrant craft that requires reimagining the status quo, finding value creation opportunities, and driving innovative and sustainable customer experiences through technology. We believe our portfolio of businesses and investments in growth and transformation will result in a company with the scale, brand, capabilities, talent, and values to succeed as the digital revolution transforms our society and our industry. About the Team This team powers real-time, intelligent banking by safely introducing, scaling, and operationalizing new Artificial Intelligence and Machine Learning capabilities across the business. Capital One Product Framework In this role, you'll be expected to demonstrate proficiency in five key areas which we consider to be the foundation for successful Product management: Human Centered - Obsesses about internal and external customer needs to reimagine and innovate product solutions Business Focused - Delivers game-changing outcomes by focusing on leverage and execution excellence Technology Driven - Leverages technology to deliver innovative and resilient solutions that enable both near term and long term value Integrated Problem Solving - Identifies and resolves complex problems to deliver outcomes while mitigating product risks Transformational Leadership - Leads cross functional teams to solve customer problems and drive organizational alignment Basic Qualifications: At least 3 years of experience working in Product Management Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, Computer Engineering, Software Engineering, Mechanical Engineering, Information Systems or a related quantitative field) A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, Computer Engineering, Software Engineering, Mechanical Engineering, Information Systems or a related quantitative field) or an MBA with a quantitative concentration Preferred Qualifications: Experience in product management for technical platforms (data science or Machine Learning preferred), MLOps, or internal developer tools. Familiarity with cloud computing environments (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Kubernetes). Demonstrated experience working in an Agile environment and managing a product backlog. At this time, Capital One will not sponsor a new applicant for employment authorization for this position The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $164,800 - $188,100 for Manager, Product Management Chicago, IL: $149,800 - $171,000 for Manager, Product Management McLean, VA: $164,800 - $188,100 for Manager, Product Management New York, NY: $179,700 - $205,100 for Manager, Product Management Richmond, VA: $149,800 - $171,000 for Manager, Product Management San Francisco, CA: $179,700 - $205,100 for Manager, Product Management Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
06/08/2026
Full time
Manager, Product Management - Enterprise AI/ML Product Management at Capital One is a booming, vibrant craft that requires reimagining the status quo, finding value creation opportunities, and driving innovative and sustainable customer experiences through technology. We believe our portfolio of businesses and investments in growth and transformation will result in a company with the scale, brand, capabilities, talent, and values to succeed as the digital revolution transforms our society and our industry. About the Team This team powers real-time, intelligent banking by safely introducing, scaling, and operationalizing new Artificial Intelligence and Machine Learning capabilities across the business. Capital One Product Framework In this role, you'll be expected to demonstrate proficiency in five key areas which we consider to be the foundation for successful Product management: Human Centered - Obsesses about internal and external customer needs to reimagine and innovate product solutions Business Focused - Delivers game-changing outcomes by focusing on leverage and execution excellence Technology Driven - Leverages technology to deliver innovative and resilient solutions that enable both near term and long term value Integrated Problem Solving - Identifies and resolves complex problems to deliver outcomes while mitigating product risks Transformational Leadership - Leads cross functional teams to solve customer problems and drive organizational alignment Basic Qualifications: At least 3 years of experience working in Product Management Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, Computer Engineering, Software Engineering, Mechanical Engineering, Information Systems or a related quantitative field) A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, Computer Engineering, Software Engineering, Mechanical Engineering, Information Systems or a related quantitative field) or an MBA with a quantitative concentration Preferred Qualifications: Experience in product management for technical platforms (data science or Machine Learning preferred), MLOps, or internal developer tools. Familiarity with cloud computing environments (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Kubernetes). Demonstrated experience working in an Agile environment and managing a product backlog. At this time, Capital One will not sponsor a new applicant for employment authorization for this position The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $164,800 - $188,100 for Manager, Product Management Chicago, IL: $149,800 - $171,000 for Manager, Product Management McLean, VA: $164,800 - $188,100 for Manager, Product Management New York, NY: $179,700 - $205,100 for Manager, Product Management Richmond, VA: $149,800 - $171,000 for Manager, Product Management San Francisco, CA: $179,700 - $205,100 for Manager, Product Management Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Lead Machine Learning Engineer (Gen AI, Python, Go, AWS) As a Capital One Machine Learning Engineer (MLE) on the GenAI Workflows Serving team, you'll be part of an Agile team dedicated to designing, building, and productionizing Generative AI applications and Agentic Workflow systems at massive scale. You'll participate in the detailed technical design, development, and implementation of complex machine learning applications leveraging cloud-native platforms. You'll focus on building robust ML serving architecture, developing high-performance application code, and ensuring the high availability, security, and low latency of our Generative AI solutions. You will collaborate closely with multiple other AI/ML teams to drive innovation and continuously apply the latest innovations and best practices in machine learning engineering. We are looking for a Machine Learning Engineer with a background as a Software Engineer. What you'll do in the role The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and deliver GenAI models and componentsthat solve complex business problems, while working in collaboration with the Product and Data Science teams. Design and implement cloud-native ML Serving Platforms leveraging technologies like Docker, Kubernetes, KNative, and KServe to ensure optimized and scalable deployment of models. Solve complex scaling and high-availability problems by writing and testing performant application code in Python and Go-lang, developing and validating ML models, and automating tests and deployment. Implement advanced MLOps and GitOps practices for continuous integration and continuous deployment (CI/CD) using tools like ArgoCD to manage the entire lifecycle of models and applications. Leverage service mesh architectures like Istio to manage traffic, enhance security, and ensure resilience for high-volume serving endpoints. Retrain, maintain, and monitor models in production. Construct optimized, scalable data pipelines to feed ML models. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Go, Scala or Java Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, Go or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer San Francisco, CA: $215,200 - $245,600 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
06/08/2026
Full time
Lead Machine Learning Engineer (Gen AI, Python, Go, AWS) As a Capital One Machine Learning Engineer (MLE) on the GenAI Workflows Serving team, you'll be part of an Agile team dedicated to designing, building, and productionizing Generative AI applications and Agentic Workflow systems at massive scale. You'll participate in the detailed technical design, development, and implementation of complex machine learning applications leveraging cloud-native platforms. You'll focus on building robust ML serving architecture, developing high-performance application code, and ensuring the high availability, security, and low latency of our Generative AI solutions. You will collaborate closely with multiple other AI/ML teams to drive innovation and continuously apply the latest innovations and best practices in machine learning engineering. We are looking for a Machine Learning Engineer with a background as a Software Engineer. What you'll do in the role The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and deliver GenAI models and componentsthat solve complex business problems, while working in collaboration with the Product and Data Science teams. Design and implement cloud-native ML Serving Platforms leveraging technologies like Docker, Kubernetes, KNative, and KServe to ensure optimized and scalable deployment of models. Solve complex scaling and high-availability problems by writing and testing performant application code in Python and Go-lang, developing and validating ML models, and automating tests and deployment. Implement advanced MLOps and GitOps practices for continuous integration and continuous deployment (CI/CD) using tools like ArgoCD to manage the entire lifecycle of models and applications. Leverage service mesh architectures like Istio to manage traffic, enhance security, and ensure resilience for high-volume serving endpoints. Retrain, maintain, and monitor models in production. Construct optimized, scalable data pipelines to feed ML models. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Go, Scala or Java Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, Go or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer San Francisco, CA: $215,200 - $245,600 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Manager, Product Management - Enterprise AI/ML Product Management at Capital One is a booming, vibrant craft that requires reimagining the status quo, finding value creation opportunities, and driving innovative and sustainable customer experiences through technology. We believe our portfolio of businesses and investments in growth and transformation will result in a company with the scale, brand, capabilities, talent, and values to succeed as the digital revolution transforms our society and our industry. About the Team This team powers real-time, intelligent banking by safely introducing, scaling, and operationalizing new Artificial Intelligence and Machine Learning capabilities across the business. Capital One Product Framework In this role, you'll be expected to demonstrate proficiency in five key areas which we consider to be the foundation for successful Product management: Human Centered - Obsesses about internal and external customer needs to reimagine and innovate product solutions Business Focused - Delivers game-changing outcomes by focusing on leverage and execution excellence Technology Driven - Leverages technology to deliver innovative and resilient solutions that enable both near term and long term value Integrated Problem Solving - Identifies and resolves complex problems to deliver outcomes while mitigating product risks Transformational Leadership - Leads cross functional teams to solve customer problems and drive organizational alignment Basic Qualifications: At least 3 years of experience working in Product Management Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, Computer Engineering, Software Engineering, Mechanical Engineering, Information Systems or a related quantitative field) A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, Computer Engineering, Software Engineering, Mechanical Engineering, Information Systems or a related quantitative field) or an MBA with a quantitative concentration Preferred Qualifications: Experience in product management for technical platforms (data science or Machine Learning preferred), MLOps, or internal developer tools. Familiarity with cloud computing environments (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Kubernetes). Demonstrated experience working in an Agile environment and managing a product backlog. At this time, Capital One will not sponsor a new applicant for employment authorization for this position The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $164,800 - $188,100 for Manager, Product Management Chicago, IL: $149,800 - $171,000 for Manager, Product Management McLean, VA: $164,800 - $188,100 for Manager, Product Management New York, NY: $179,700 - $205,100 for Manager, Product Management Richmond, VA: $149,800 - $171,000 for Manager, Product Management San Francisco, CA: $179,700 - $205,100 for Manager, Product Management Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
06/08/2026
Full time
Manager, Product Management - Enterprise AI/ML Product Management at Capital One is a booming, vibrant craft that requires reimagining the status quo, finding value creation opportunities, and driving innovative and sustainable customer experiences through technology. We believe our portfolio of businesses and investments in growth and transformation will result in a company with the scale, brand, capabilities, talent, and values to succeed as the digital revolution transforms our society and our industry. About the Team This team powers real-time, intelligent banking by safely introducing, scaling, and operationalizing new Artificial Intelligence and Machine Learning capabilities across the business. Capital One Product Framework In this role, you'll be expected to demonstrate proficiency in five key areas which we consider to be the foundation for successful Product management: Human Centered - Obsesses about internal and external customer needs to reimagine and innovate product solutions Business Focused - Delivers game-changing outcomes by focusing on leverage and execution excellence Technology Driven - Leverages technology to deliver innovative and resilient solutions that enable both near term and long term value Integrated Problem Solving - Identifies and resolves complex problems to deliver outcomes while mitigating product risks Transformational Leadership - Leads cross functional teams to solve customer problems and drive organizational alignment Basic Qualifications: At least 3 years of experience working in Product Management Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, Computer Engineering, Software Engineering, Mechanical Engineering, Information Systems or a related quantitative field) A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, Computer Engineering, Software Engineering, Mechanical Engineering, Information Systems or a related quantitative field) or an MBA with a quantitative concentration Preferred Qualifications: Experience in product management for technical platforms (data science or Machine Learning preferred), MLOps, or internal developer tools. Familiarity with cloud computing environments (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Kubernetes). Demonstrated experience working in an Agile environment and managing a product backlog. At this time, Capital One will not sponsor a new applicant for employment authorization for this position The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $164,800 - $188,100 for Manager, Product Management Chicago, IL: $149,800 - $171,000 for Manager, Product Management McLean, VA: $164,800 - $188,100 for Manager, Product Management New York, NY: $179,700 - $205,100 for Manager, Product Management Richmond, VA: $149,800 - $171,000 for Manager, Product Management San Francisco, CA: $179,700 - $205,100 for Manager, Product Management Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Job DescriptionJob Description Revolutional delivers advanced technology solutions and mission support to federal agencies across civilian, health, and national security environments. We apply modern capabilities, including AI/ML, cloud, cybersecurity, and IT modernization to solve complex challenges, enable faster and more secure operations, and drive measurable mission outcomes. We are redefining how federal technology gets built and delivered by operating with a product mindset, prioritizing speed, ownership, and execution over bureaucracy. Lead Data Scientist Location: Suitland, MD (Hybrid) Terms: Full-time Clearance/Work Authorization: U.S. Citizenship with the ability to obtain and maintain a Public Trust is required Travel: % Project Description This position supports Revolutional's federal customer as part of an application transformation and modernization initiative. This program is driving a large-scale transformation of systems into a data-centric, cloud-native ecosystem capable of supporting high-volume, near real-time data processing and advanced analytics. The work includes modernization of legacy applications, development of new cloud-native solutions, and implementation of DevSecOps and scaled Agile practices across the organization. The core challenge: orchestrating complex, multi-contractor delivery while transforming both technology and operating models without disrupting mission-critical operations. Position Description As a Lead Data Scientist at Revolutional, you will define and drive enterprise data science and AI/ML strategy across a large-scale federal modernization program. You will lead efforts spanning advanced analytics, machine learning, MLOps, AI governance, and operational analytics integration across complex enterprise systems. This role requires close collaboration with data engineering, architecture, application development, and operational teams to ensure AI/ML capabilities are production-ready, scalable, explainable, and integrated into enterprise workflows. You will operate at both strategic and hands-on levels guiding technical direction, developing advanced models, and ensuring analytics solutions deliver measurable mission impact. Responsibilities Provide technical leadership across enterprise data science and AI/ML initiatives within a large-scale modernization program Design, develop, validate, deploy, monitor, and scale machine learning and advanced analytics solutions in production environments Lead implementation of MLOps practices supporting model lifecycle management, automation, observability, and continuous improvement Apply advanced data science techniques including NLP, LLMs, deep learning, reinforcement learning, anomaly detection, and time series analysis Design and support event-driven analytics and real-time/streaming ML pipelines Collaborate with data engineers, architects, application teams, and SMEs to integrate AI/ML capabilities into enterprise systems and operational workflows Support system-of-systems (SoS) integrations across multiple systems, vendors, contractors, and interdependent platforms Establish AI governance frameworks supporting fairness, bias mitigation, explainability, transparency, and compliance with standards such as the NIST AI Risk Management Framework Develop reproducible analytics workflows, technical documentation, analysis plans, dashboards, and reporting deliverables Support DataOps and Agile data science practices including iterative development, pipeline automation, CI/CD integration, and collaborative model delivery Ensure analytics solutions align with enterprise security, privacy, and compliance requirements Drive improvements in data quality, validation, accessibility, and operational analytics reliability Present findings, recommendations, and technical approaches to executive leadership and stakeholders Mentor data scientists and analytics teams while promoting best practices across the organization Technical Environment Cloud-native AI/ML and analytics environments (AWS, Azure) Distributed data platforms and enterprise analytics ecosystems Python, R, Spark, TensorFlow, PyTorch, Databricks, and related ML frameworks MLOps pipelines, model deployment platforms, and automation frameworks Real-time streaming and event-driven analytics systems DevSecOps pipelines and CI/CD automation practices DataOps and Agile/SAFe delivery environments APIs, distributed integrations, and enterprise data platforms Collaboration and delivery tools (Git, Jira, Confluence) High-volume, near real-time processing environments What You Bring (Requirements) Baseline Requirements U.S. Citizenship with the ability to obtain a Public Trust PhD in Data Science, Computer Science, Statistics, Mathematics, or related field 15+ years of experience in data science, AI/ML, advanced analytics, or enterprise modernization initiatives Proven experience leading AI/ML and analytics efforts across large-scale, complex systems Ability to obtain and maintain a Public Trust clearance Technical Capabilities Deep expertise in machine learning, statistical modeling, and advanced analytics techniques Experience implementing end-to-end MLOps pipelines including model training, validation, deployment, monitoring, and scaling Experience with NLP, LLMs, deep learning, reinforcement learning, anomaly detection, and time series analytics Experience designing and supporting real-time or streaming analytics architectures Experience integrating AI/ML solutions across system-of-systems (SoS) environments and distributed enterprise platforms Experience implementing AI governance frameworks addressing explainability, fairness, transparency, and bias mitigation Experience with large-scale distributed data environments and cloud-native analytics platforms Experience with DataOps, CI/CD integration, and Agile/SAFe delivery models Strong experience with Python, R, Spark, TensorFlow, PyTorch, Databricks, and related AI/ML technologies Experience developing dashboards, technical reports, analysis plans, and reproducible analytics workflows Experience collaborating across engineering, architecture, application, and operational teams at enterprise scale Core Strengths Strong ownership mindset with accountability for enterprise AI/ML outcomes Ability to translate complex analytical findings into actionable business and mission insights Strategic thinker capable of balancing innovation, governance, and operational realities Effective communication across technical, operational, and executive stakeholders Strong leadership and mentoring capabilities across data science and analytics teams Ability to operate in complex, fast-moving, multi-contractor delivery environments Nice to Have (Differentiators) Experience supporting statistical and similarly large-scale federal modernization programs Experience implementing enterprise AI governance or responsible AI initiatives Experience with event-driven architectures, streaming analytics, or operational AI systems Experience supporting large-scale data modernization or enterprise analytics transformation efforts Experience working within DevSecOps-enabled AI/ML delivery environments _ Here at Revolutional we are pleased to have been repeatedly recognized for our outstanding work culture, the innovative work we do, and the employees on our team who make a difference each day. Some of these recognitions include: Recognized as a Top 20 "Best Place to Work in Virginia" Recipient of Department of Labor's HireVets Gold Medallion Great Place to Work Certification for five years running A Virginia Chamber of Commerce Fantastic 50 company A Northern Virginia Technology Council Tech 100 company Inc. 5000 list of fastest growing companies for eleven years Two-time SBA SBIR Tibbett's Award winner Virginia Values Veterans (V3) Certification We recognize that every bit of our success is the result of our teams of hard-working, motivated, and innovative professionals who are proud to call themselves part of the Revolutional family! In addition to competitive compensation, a family-focused culture, and a dynamic, productive work environment, we offer all full-time employees a variety of benefits including, but not limited to Traditional and HSA- eligible medical insurance plans 100% employer-paid dental and vision insurance options 100% employer-sponsored STD, LTD, and life insurance 5% 401(k) company matching Flexible-schedules and teleworking options Paid holidays and PTO Accrual Plans Paid Parental Leave Professional development and career growth opportunities Team and company-wide events, recognition, and appreciation and so much more! Check out our Revolutional LinkedIn to find out a little more about who we are and if we are the right next step for your career! Revolutional is an Equal Opportunity Employer providing equal employment opportunity to all employees and applicants for employment without regard to race, color, religion, national origin, age, gender . click apply for full job details
06/08/2026
Full time
Job DescriptionJob Description Revolutional delivers advanced technology solutions and mission support to federal agencies across civilian, health, and national security environments. We apply modern capabilities, including AI/ML, cloud, cybersecurity, and IT modernization to solve complex challenges, enable faster and more secure operations, and drive measurable mission outcomes. We are redefining how federal technology gets built and delivered by operating with a product mindset, prioritizing speed, ownership, and execution over bureaucracy. Lead Data Scientist Location: Suitland, MD (Hybrid) Terms: Full-time Clearance/Work Authorization: U.S. Citizenship with the ability to obtain and maintain a Public Trust is required Travel: % Project Description This position supports Revolutional's federal customer as part of an application transformation and modernization initiative. This program is driving a large-scale transformation of systems into a data-centric, cloud-native ecosystem capable of supporting high-volume, near real-time data processing and advanced analytics. The work includes modernization of legacy applications, development of new cloud-native solutions, and implementation of DevSecOps and scaled Agile practices across the organization. The core challenge: orchestrating complex, multi-contractor delivery while transforming both technology and operating models without disrupting mission-critical operations. Position Description As a Lead Data Scientist at Revolutional, you will define and drive enterprise data science and AI/ML strategy across a large-scale federal modernization program. You will lead efforts spanning advanced analytics, machine learning, MLOps, AI governance, and operational analytics integration across complex enterprise systems. This role requires close collaboration with data engineering, architecture, application development, and operational teams to ensure AI/ML capabilities are production-ready, scalable, explainable, and integrated into enterprise workflows. You will operate at both strategic and hands-on levels guiding technical direction, developing advanced models, and ensuring analytics solutions deliver measurable mission impact. Responsibilities Provide technical leadership across enterprise data science and AI/ML initiatives within a large-scale modernization program Design, develop, validate, deploy, monitor, and scale machine learning and advanced analytics solutions in production environments Lead implementation of MLOps practices supporting model lifecycle management, automation, observability, and continuous improvement Apply advanced data science techniques including NLP, LLMs, deep learning, reinforcement learning, anomaly detection, and time series analysis Design and support event-driven analytics and real-time/streaming ML pipelines Collaborate with data engineers, architects, application teams, and SMEs to integrate AI/ML capabilities into enterprise systems and operational workflows Support system-of-systems (SoS) integrations across multiple systems, vendors, contractors, and interdependent platforms Establish AI governance frameworks supporting fairness, bias mitigation, explainability, transparency, and compliance with standards such as the NIST AI Risk Management Framework Develop reproducible analytics workflows, technical documentation, analysis plans, dashboards, and reporting deliverables Support DataOps and Agile data science practices including iterative development, pipeline automation, CI/CD integration, and collaborative model delivery Ensure analytics solutions align with enterprise security, privacy, and compliance requirements Drive improvements in data quality, validation, accessibility, and operational analytics reliability Present findings, recommendations, and technical approaches to executive leadership and stakeholders Mentor data scientists and analytics teams while promoting best practices across the organization Technical Environment Cloud-native AI/ML and analytics environments (AWS, Azure) Distributed data platforms and enterprise analytics ecosystems Python, R, Spark, TensorFlow, PyTorch, Databricks, and related ML frameworks MLOps pipelines, model deployment platforms, and automation frameworks Real-time streaming and event-driven analytics systems DevSecOps pipelines and CI/CD automation practices DataOps and Agile/SAFe delivery environments APIs, distributed integrations, and enterprise data platforms Collaboration and delivery tools (Git, Jira, Confluence) High-volume, near real-time processing environments What You Bring (Requirements) Baseline Requirements U.S. Citizenship with the ability to obtain a Public Trust PhD in Data Science, Computer Science, Statistics, Mathematics, or related field 15+ years of experience in data science, AI/ML, advanced analytics, or enterprise modernization initiatives Proven experience leading AI/ML and analytics efforts across large-scale, complex systems Ability to obtain and maintain a Public Trust clearance Technical Capabilities Deep expertise in machine learning, statistical modeling, and advanced analytics techniques Experience implementing end-to-end MLOps pipelines including model training, validation, deployment, monitoring, and scaling Experience with NLP, LLMs, deep learning, reinforcement learning, anomaly detection, and time series analytics Experience designing and supporting real-time or streaming analytics architectures Experience integrating AI/ML solutions across system-of-systems (SoS) environments and distributed enterprise platforms Experience implementing AI governance frameworks addressing explainability, fairness, transparency, and bias mitigation Experience with large-scale distributed data environments and cloud-native analytics platforms Experience with DataOps, CI/CD integration, and Agile/SAFe delivery models Strong experience with Python, R, Spark, TensorFlow, PyTorch, Databricks, and related AI/ML technologies Experience developing dashboards, technical reports, analysis plans, and reproducible analytics workflows Experience collaborating across engineering, architecture, application, and operational teams at enterprise scale Core Strengths Strong ownership mindset with accountability for enterprise AI/ML outcomes Ability to translate complex analytical findings into actionable business and mission insights Strategic thinker capable of balancing innovation, governance, and operational realities Effective communication across technical, operational, and executive stakeholders Strong leadership and mentoring capabilities across data science and analytics teams Ability to operate in complex, fast-moving, multi-contractor delivery environments Nice to Have (Differentiators) Experience supporting statistical and similarly large-scale federal modernization programs Experience implementing enterprise AI governance or responsible AI initiatives Experience with event-driven architectures, streaming analytics, or operational AI systems Experience supporting large-scale data modernization or enterprise analytics transformation efforts Experience working within DevSecOps-enabled AI/ML delivery environments _ Here at Revolutional we are pleased to have been repeatedly recognized for our outstanding work culture, the innovative work we do, and the employees on our team who make a difference each day. Some of these recognitions include: Recognized as a Top 20 "Best Place to Work in Virginia" Recipient of Department of Labor's HireVets Gold Medallion Great Place to Work Certification for five years running A Virginia Chamber of Commerce Fantastic 50 company A Northern Virginia Technology Council Tech 100 company Inc. 5000 list of fastest growing companies for eleven years Two-time SBA SBIR Tibbett's Award winner Virginia Values Veterans (V3) Certification We recognize that every bit of our success is the result of our teams of hard-working, motivated, and innovative professionals who are proud to call themselves part of the Revolutional family! In addition to competitive compensation, a family-focused culture, and a dynamic, productive work environment, we offer all full-time employees a variety of benefits including, but not limited to Traditional and HSA- eligible medical insurance plans 100% employer-paid dental and vision insurance options 100% employer-sponsored STD, LTD, and life insurance 5% 401(k) company matching Flexible-schedules and teleworking options Paid holidays and PTO Accrual Plans Paid Parental Leave Professional development and career growth opportunities Team and company-wide events, recognition, and appreciation and so much more! Check out our Revolutional LinkedIn to find out a little more about who we are and if we are the right next step for your career! Revolutional is an Equal Opportunity Employer providing equal employment opportunity to all employees and applicants for employment without regard to race, color, religion, national origin, age, gender . click apply for full job details
Job DescriptionJob Description Revolutional delivers advanced technology solutions and mission support to federal agencies across civilian, health, and national security environments. We apply modern capabilities, including AI/ML, cloud, cybersecurity, and IT modernization to solve complex challenges, enable faster and more secure operations, and drive measurable mission outcomes. We are redefining how federal technology gets built and delivered by operating with a product mindset, prioritizing speed, ownership, and execution over bureaucracy. Lead Data Scientist Location: Suitland, MD (Hybrid) Terms: Full-time Clearance/Work Authorization: U.S. Citizenship with the ability to obtain and maintain a Public Trust is required Travel: % Project Description This position supports Revolutional's federal customer as part of an application transformation and modernization initiative. This program is driving a large-scale transformation of systems into a data-centric, cloud-native ecosystem capable of supporting high-volume, near real-time data processing and advanced analytics. The work includes modernization of legacy applications, development of new cloud-native solutions, and implementation of DevSecOps and scaled Agile practices across the organization. The core challenge: orchestrating complex, multi-contractor delivery while transforming both technology and operating models without disrupting mission-critical operations. Position Description As a Lead Data Scientist at Revolutional, you will define and drive enterprise data science and AI/ML strategy across a large-scale federal modernization program. You will lead efforts spanning advanced analytics, machine learning, MLOps, AI governance, and operational analytics integration across complex enterprise systems. This role requires close collaboration with data engineering, architecture, application development, and operational teams to ensure AI/ML capabilities are production-ready, scalable, explainable, and integrated into enterprise workflows. You will operate at both strategic and hands-on levels guiding technical direction, developing advanced models, and ensuring analytics solutions deliver measurable mission impact. Responsibilities Provide technical leadership across enterprise data science and AI/ML initiatives within a large-scale modernization program Design, develop, validate, deploy, monitor, and scale machine learning and advanced analytics solutions in production environments Lead implementation of MLOps practices supporting model lifecycle management, automation, observability, and continuous improvement Apply advanced data science techniques including NLP, LLMs, deep learning, reinforcement learning, anomaly detection, and time series analysis Design and support event-driven analytics and real-time/streaming ML pipelines Collaborate with data engineers, architects, application teams, and SMEs to integrate AI/ML capabilities into enterprise systems and operational workflows Support system-of-systems (SoS) integrations across multiple systems, vendors, contractors, and interdependent platforms Establish AI governance frameworks supporting fairness, bias mitigation, explainability, transparency, and compliance with standards such as the NIST AI Risk Management Framework Develop reproducible analytics workflows, technical documentation, analysis plans, dashboards, and reporting deliverables Support DataOps and Agile data science practices including iterative development, pipeline automation, CI/CD integration, and collaborative model delivery Ensure analytics solutions align with enterprise security, privacy, and compliance requirements Drive improvements in data quality, validation, accessibility, and operational analytics reliability Present findings, recommendations, and technical approaches to executive leadership and stakeholders Mentor data scientists and analytics teams while promoting best practices across the organization Technical Environment Cloud-native AI/ML and analytics environments (AWS, Azure) Distributed data platforms and enterprise analytics ecosystems Python, R, Spark, TensorFlow, PyTorch, Databricks, and related ML frameworks MLOps pipelines, model deployment platforms, and automation frameworks Real-time streaming and event-driven analytics systems DevSecOps pipelines and CI/CD automation practices DataOps and Agile/SAFe delivery environments APIs, distributed integrations, and enterprise data platforms Collaboration and delivery tools (Git, Jira, Confluence) High-volume, near real-time processing environments What You Bring (Requirements) Baseline Requirements U.S. Citizenship with the ability to obtain a Public Trust PhD in Data Science, Computer Science, Statistics, Mathematics, or related field 15+ years of experience in data science, AI/ML, advanced analytics, or enterprise modernization initiatives Proven experience leading AI/ML and analytics efforts across large-scale, complex systems Ability to obtain and maintain a Public Trust clearance Technical Capabilities Deep expertise in machine learning, statistical modeling, and advanced analytics techniques Experience implementing end-to-end MLOps pipelines including model training, validation, deployment, monitoring, and scaling Experience with NLP, LLMs, deep learning, reinforcement learning, anomaly detection, and time series analytics Experience designing and supporting real-time or streaming analytics architectures Experience integrating AI/ML solutions across system-of-systems (SoS) environments and distributed enterprise platforms Experience implementing AI governance frameworks addressing explainability, fairness, transparency, and bias mitigation Experience with large-scale distributed data environments and cloud-native analytics platforms Experience with DataOps, CI/CD integration, and Agile/SAFe delivery models Strong experience with Python, R, Spark, TensorFlow, PyTorch, Databricks, and related AI/ML technologies Experience developing dashboards, technical reports, analysis plans, and reproducible analytics workflows Experience collaborating across engineering, architecture, application, and operational teams at enterprise scale Core Strengths Strong ownership mindset with accountability for enterprise AI/ML outcomes Ability to translate complex analytical findings into actionable business and mission insights Strategic thinker capable of balancing innovation, governance, and operational realities Effective communication across technical, operational, and executive stakeholders Strong leadership and mentoring capabilities across data science and analytics teams Ability to operate in complex, fast-moving, multi-contractor delivery environments Nice to Have (Differentiators) Experience supporting statistical and similarly large-scale federal modernization programs Experience implementing enterprise AI governance or responsible AI initiatives Experience with event-driven architectures, streaming analytics, or operational AI systems Experience supporting large-scale data modernization or enterprise analytics transformation efforts Experience working within DevSecOps-enabled AI/ML delivery environments _ Here at Revolutional we are pleased to have been repeatedly recognized for our outstanding work culture, the innovative work we do, and the employees on our team who make a difference each day. Some of these recognitions include: Recognized as a Top 20 "Best Place to Work in Virginia" Recipient of Department of Labor's HireVets Gold Medallion Great Place to Work Certification for five years running A Virginia Chamber of Commerce Fantastic 50 company A Northern Virginia Technology Council Tech 100 company Inc. 5000 list of fastest growing companies for eleven years Two-time SBA SBIR Tibbett's Award winner Virginia Values Veterans (V3) Certification We recognize that every bit of our success is the result of our teams of hard-working, motivated, and innovative professionals who are proud to call themselves part of the Revolutional family! In addition to competitive compensation, a family-focused culture, and a dynamic, productive work environment, we offer all full-time employees a variety of benefits including, but not limited to Traditional and HSA- eligible medical insurance plans 100% employer-paid dental and vision insurance options 100% employer-sponsored STD, LTD, and life insurance 5% 401(k) company matching Flexible-schedules and teleworking options Paid holidays and PTO Accrual Plans Paid Parental Leave Professional development and career growth opportunities Team and company-wide events, recognition, and appreciation and so much more! Check out our Revolutional LinkedIn to find out a little more about who we are and if we are the right next step for your career! Revolutional is an Equal Opportunity Employer providing equal employment opportunity to all employees and applicants for employment without regard to race, color, religion, national origin, age, gender . click apply for full job details
06/08/2026
Full time
Job DescriptionJob Description Revolutional delivers advanced technology solutions and mission support to federal agencies across civilian, health, and national security environments. We apply modern capabilities, including AI/ML, cloud, cybersecurity, and IT modernization to solve complex challenges, enable faster and more secure operations, and drive measurable mission outcomes. We are redefining how federal technology gets built and delivered by operating with a product mindset, prioritizing speed, ownership, and execution over bureaucracy. Lead Data Scientist Location: Suitland, MD (Hybrid) Terms: Full-time Clearance/Work Authorization: U.S. Citizenship with the ability to obtain and maintain a Public Trust is required Travel: % Project Description This position supports Revolutional's federal customer as part of an application transformation and modernization initiative. This program is driving a large-scale transformation of systems into a data-centric, cloud-native ecosystem capable of supporting high-volume, near real-time data processing and advanced analytics. The work includes modernization of legacy applications, development of new cloud-native solutions, and implementation of DevSecOps and scaled Agile practices across the organization. The core challenge: orchestrating complex, multi-contractor delivery while transforming both technology and operating models without disrupting mission-critical operations. Position Description As a Lead Data Scientist at Revolutional, you will define and drive enterprise data science and AI/ML strategy across a large-scale federal modernization program. You will lead efforts spanning advanced analytics, machine learning, MLOps, AI governance, and operational analytics integration across complex enterprise systems. This role requires close collaboration with data engineering, architecture, application development, and operational teams to ensure AI/ML capabilities are production-ready, scalable, explainable, and integrated into enterprise workflows. You will operate at both strategic and hands-on levels guiding technical direction, developing advanced models, and ensuring analytics solutions deliver measurable mission impact. Responsibilities Provide technical leadership across enterprise data science and AI/ML initiatives within a large-scale modernization program Design, develop, validate, deploy, monitor, and scale machine learning and advanced analytics solutions in production environments Lead implementation of MLOps practices supporting model lifecycle management, automation, observability, and continuous improvement Apply advanced data science techniques including NLP, LLMs, deep learning, reinforcement learning, anomaly detection, and time series analysis Design and support event-driven analytics and real-time/streaming ML pipelines Collaborate with data engineers, architects, application teams, and SMEs to integrate AI/ML capabilities into enterprise systems and operational workflows Support system-of-systems (SoS) integrations across multiple systems, vendors, contractors, and interdependent platforms Establish AI governance frameworks supporting fairness, bias mitigation, explainability, transparency, and compliance with standards such as the NIST AI Risk Management Framework Develop reproducible analytics workflows, technical documentation, analysis plans, dashboards, and reporting deliverables Support DataOps and Agile data science practices including iterative development, pipeline automation, CI/CD integration, and collaborative model delivery Ensure analytics solutions align with enterprise security, privacy, and compliance requirements Drive improvements in data quality, validation, accessibility, and operational analytics reliability Present findings, recommendations, and technical approaches to executive leadership and stakeholders Mentor data scientists and analytics teams while promoting best practices across the organization Technical Environment Cloud-native AI/ML and analytics environments (AWS, Azure) Distributed data platforms and enterprise analytics ecosystems Python, R, Spark, TensorFlow, PyTorch, Databricks, and related ML frameworks MLOps pipelines, model deployment platforms, and automation frameworks Real-time streaming and event-driven analytics systems DevSecOps pipelines and CI/CD automation practices DataOps and Agile/SAFe delivery environments APIs, distributed integrations, and enterprise data platforms Collaboration and delivery tools (Git, Jira, Confluence) High-volume, near real-time processing environments What You Bring (Requirements) Baseline Requirements U.S. Citizenship with the ability to obtain a Public Trust PhD in Data Science, Computer Science, Statistics, Mathematics, or related field 15+ years of experience in data science, AI/ML, advanced analytics, or enterprise modernization initiatives Proven experience leading AI/ML and analytics efforts across large-scale, complex systems Ability to obtain and maintain a Public Trust clearance Technical Capabilities Deep expertise in machine learning, statistical modeling, and advanced analytics techniques Experience implementing end-to-end MLOps pipelines including model training, validation, deployment, monitoring, and scaling Experience with NLP, LLMs, deep learning, reinforcement learning, anomaly detection, and time series analytics Experience designing and supporting real-time or streaming analytics architectures Experience integrating AI/ML solutions across system-of-systems (SoS) environments and distributed enterprise platforms Experience implementing AI governance frameworks addressing explainability, fairness, transparency, and bias mitigation Experience with large-scale distributed data environments and cloud-native analytics platforms Experience with DataOps, CI/CD integration, and Agile/SAFe delivery models Strong experience with Python, R, Spark, TensorFlow, PyTorch, Databricks, and related AI/ML technologies Experience developing dashboards, technical reports, analysis plans, and reproducible analytics workflows Experience collaborating across engineering, architecture, application, and operational teams at enterprise scale Core Strengths Strong ownership mindset with accountability for enterprise AI/ML outcomes Ability to translate complex analytical findings into actionable business and mission insights Strategic thinker capable of balancing innovation, governance, and operational realities Effective communication across technical, operational, and executive stakeholders Strong leadership and mentoring capabilities across data science and analytics teams Ability to operate in complex, fast-moving, multi-contractor delivery environments Nice to Have (Differentiators) Experience supporting statistical and similarly large-scale federal modernization programs Experience implementing enterprise AI governance or responsible AI initiatives Experience with event-driven architectures, streaming analytics, or operational AI systems Experience supporting large-scale data modernization or enterprise analytics transformation efforts Experience working within DevSecOps-enabled AI/ML delivery environments _ Here at Revolutional we are pleased to have been repeatedly recognized for our outstanding work culture, the innovative work we do, and the employees on our team who make a difference each day. Some of these recognitions include: Recognized as a Top 20 "Best Place to Work in Virginia" Recipient of Department of Labor's HireVets Gold Medallion Great Place to Work Certification for five years running A Virginia Chamber of Commerce Fantastic 50 company A Northern Virginia Technology Council Tech 100 company Inc. 5000 list of fastest growing companies for eleven years Two-time SBA SBIR Tibbett's Award winner Virginia Values Veterans (V3) Certification We recognize that every bit of our success is the result of our teams of hard-working, motivated, and innovative professionals who are proud to call themselves part of the Revolutional family! In addition to competitive compensation, a family-focused culture, and a dynamic, productive work environment, we offer all full-time employees a variety of benefits including, but not limited to Traditional and HSA- eligible medical insurance plans 100% employer-paid dental and vision insurance options 100% employer-sponsored STD, LTD, and life insurance 5% 401(k) company matching Flexible-schedules and teleworking options Paid holidays and PTO Accrual Plans Paid Parental Leave Professional development and career growth opportunities Team and company-wide events, recognition, and appreciation and so much more! Check out our Revolutional LinkedIn to find out a little more about who we are and if we are the right next step for your career! Revolutional is an Equal Opportunity Employer providing equal employment opportunity to all employees and applicants for employment without regard to race, color, religion, national origin, age, gender . click apply for full job details
Job DescriptionJob Description Revolutional delivers advanced technology solutions and mission support to federal agencies across civilian, health, and national security environments. We apply modern capabilities, including AI/ML, cloud, cybersecurity, and IT modernization to solve complex challenges, enable faster and more secure operations, and drive measurable mission outcomes. We are redefining how federal technology gets built and delivered by operating with a product mindset, prioritizing speed, ownership, and execution over bureaucracy. Lead Data Scientist Location: Suitland, MD (Hybrid) Terms: Full-time Clearance/Work Authorization: U.S. Citizenship with the ability to obtain and maintain a Public Trust is required Travel: % Project Description This position supports Revolutional's federal customer as part of an application transformation and modernization initiative. This program is driving a large-scale transformation of systems into a data-centric, cloud-native ecosystem capable of supporting high-volume, near real-time data processing and advanced analytics. The work includes modernization of legacy applications, development of new cloud-native solutions, and implementation of DevSecOps and scaled Agile practices across the organization. The core challenge: orchestrating complex, multi-contractor delivery while transforming both technology and operating models without disrupting mission-critical operations. Position Description As a Lead Data Scientist at Revolutional, you will define and drive enterprise data science and AI/ML strategy across a large-scale federal modernization program. You will lead efforts spanning advanced analytics, machine learning, MLOps, AI governance, and operational analytics integration across complex enterprise systems. This role requires close collaboration with data engineering, architecture, application development, and operational teams to ensure AI/ML capabilities are production-ready, scalable, explainable, and integrated into enterprise workflows. You will operate at both strategic and hands-on levels guiding technical direction, developing advanced models, and ensuring analytics solutions deliver measurable mission impact. Responsibilities Provide technical leadership across enterprise data science and AI/ML initiatives within a large-scale modernization program Design, develop, validate, deploy, monitor, and scale machine learning and advanced analytics solutions in production environments Lead implementation of MLOps practices supporting model lifecycle management, automation, observability, and continuous improvement Apply advanced data science techniques including NLP, LLMs, deep learning, reinforcement learning, anomaly detection, and time series analysis Design and support event-driven analytics and real-time/streaming ML pipelines Collaborate with data engineers, architects, application teams, and SMEs to integrate AI/ML capabilities into enterprise systems and operational workflows Support system-of-systems (SoS) integrations across multiple systems, vendors, contractors, and interdependent platforms Establish AI governance frameworks supporting fairness, bias mitigation, explainability, transparency, and compliance with standards such as the NIST AI Risk Management Framework Develop reproducible analytics workflows, technical documentation, analysis plans, dashboards, and reporting deliverables Support DataOps and Agile data science practices including iterative development, pipeline automation, CI/CD integration, and collaborative model delivery Ensure analytics solutions align with enterprise security, privacy, and compliance requirements Drive improvements in data quality, validation, accessibility, and operational analytics reliability Present findings, recommendations, and technical approaches to executive leadership and stakeholders Mentor data scientists and analytics teams while promoting best practices across the organization Technical Environment Cloud-native AI/ML and analytics environments (AWS, Azure) Distributed data platforms and enterprise analytics ecosystems Python, R, Spark, TensorFlow, PyTorch, Databricks, and related ML frameworks MLOps pipelines, model deployment platforms, and automation frameworks Real-time streaming and event-driven analytics systems DevSecOps pipelines and CI/CD automation practices DataOps and Agile/SAFe delivery environments APIs, distributed integrations, and enterprise data platforms Collaboration and delivery tools (Git, Jira, Confluence) High-volume, near real-time processing environments What You Bring (Requirements) Baseline Requirements U.S. Citizenship with the ability to obtain a Public Trust PhD in Data Science, Computer Science, Statistics, Mathematics, or related field 15+ years of experience in data science, AI/ML, advanced analytics, or enterprise modernization initiatives Proven experience leading AI/ML and analytics efforts across large-scale, complex systems Ability to obtain and maintain a Public Trust clearance Technical Capabilities Deep expertise in machine learning, statistical modeling, and advanced analytics techniques Experience implementing end-to-end MLOps pipelines including model training, validation, deployment, monitoring, and scaling Experience with NLP, LLMs, deep learning, reinforcement learning, anomaly detection, and time series analytics Experience designing and supporting real-time or streaming analytics architectures Experience integrating AI/ML solutions across system-of-systems (SoS) environments and distributed enterprise platforms Experience implementing AI governance frameworks addressing explainability, fairness, transparency, and bias mitigation Experience with large-scale distributed data environments and cloud-native analytics platforms Experience with DataOps, CI/CD integration, and Agile/SAFe delivery models Strong experience with Python, R, Spark, TensorFlow, PyTorch, Databricks, and related AI/ML technologies Experience developing dashboards, technical reports, analysis plans, and reproducible analytics workflows Experience collaborating across engineering, architecture, application, and operational teams at enterprise scale Core Strengths Strong ownership mindset with accountability for enterprise AI/ML outcomes Ability to translate complex analytical findings into actionable business and mission insights Strategic thinker capable of balancing innovation, governance, and operational realities Effective communication across technical, operational, and executive stakeholders Strong leadership and mentoring capabilities across data science and analytics teams Ability to operate in complex, fast-moving, multi-contractor delivery environments Nice to Have (Differentiators) Experience supporting statistical and similarly large-scale federal modernization programs Experience implementing enterprise AI governance or responsible AI initiatives Experience with event-driven architectures, streaming analytics, or operational AI systems Experience supporting large-scale data modernization or enterprise analytics transformation efforts Experience working within DevSecOps-enabled AI/ML delivery environments _ Here at Revolutional we are pleased to have been repeatedly recognized for our outstanding work culture, the innovative work we do, and the employees on our team who make a difference each day. Some of these recognitions include: Recognized as a Top 20 "Best Place to Work in Virginia" Recipient of Department of Labor's HireVets Gold Medallion Great Place to Work Certification for five years running A Virginia Chamber of Commerce Fantastic 50 company A Northern Virginia Technology Council Tech 100 company Inc. 5000 list of fastest growing companies for eleven years Two-time SBA SBIR Tibbett's Award winner Virginia Values Veterans (V3) Certification We recognize that every bit of our success is the result of our teams of hard-working, motivated, and innovative professionals who are proud to call themselves part of the Revolutional family! In addition to competitive compensation, a family-focused culture, and a dynamic, productive work environment, we offer all full-time employees a variety of benefits including, but not limited to Traditional and HSA- eligible medical insurance plans 100% employer-paid dental and vision insurance options 100% employer-sponsored STD, LTD, and life insurance 5% 401(k) company matching Flexible-schedules and teleworking options Paid holidays and PTO Accrual Plans Paid Parental Leave Professional development and career growth opportunities Team and company-wide events, recognition, and appreciation and so much more! Check out our Revolutional LinkedIn to find out a little more about who we are and if we are the right next step for your career! Revolutional is an Equal Opportunity Employer providing equal employment opportunity to all employees and applicants for employment without regard to race, color, religion, national origin, age, gender . click apply for full job details
06/08/2026
Full time
Job DescriptionJob Description Revolutional delivers advanced technology solutions and mission support to federal agencies across civilian, health, and national security environments. We apply modern capabilities, including AI/ML, cloud, cybersecurity, and IT modernization to solve complex challenges, enable faster and more secure operations, and drive measurable mission outcomes. We are redefining how federal technology gets built and delivered by operating with a product mindset, prioritizing speed, ownership, and execution over bureaucracy. Lead Data Scientist Location: Suitland, MD (Hybrid) Terms: Full-time Clearance/Work Authorization: U.S. Citizenship with the ability to obtain and maintain a Public Trust is required Travel: % Project Description This position supports Revolutional's federal customer as part of an application transformation and modernization initiative. This program is driving a large-scale transformation of systems into a data-centric, cloud-native ecosystem capable of supporting high-volume, near real-time data processing and advanced analytics. The work includes modernization of legacy applications, development of new cloud-native solutions, and implementation of DevSecOps and scaled Agile practices across the organization. The core challenge: orchestrating complex, multi-contractor delivery while transforming both technology and operating models without disrupting mission-critical operations. Position Description As a Lead Data Scientist at Revolutional, you will define and drive enterprise data science and AI/ML strategy across a large-scale federal modernization program. You will lead efforts spanning advanced analytics, machine learning, MLOps, AI governance, and operational analytics integration across complex enterprise systems. This role requires close collaboration with data engineering, architecture, application development, and operational teams to ensure AI/ML capabilities are production-ready, scalable, explainable, and integrated into enterprise workflows. You will operate at both strategic and hands-on levels guiding technical direction, developing advanced models, and ensuring analytics solutions deliver measurable mission impact. Responsibilities Provide technical leadership across enterprise data science and AI/ML initiatives within a large-scale modernization program Design, develop, validate, deploy, monitor, and scale machine learning and advanced analytics solutions in production environments Lead implementation of MLOps practices supporting model lifecycle management, automation, observability, and continuous improvement Apply advanced data science techniques including NLP, LLMs, deep learning, reinforcement learning, anomaly detection, and time series analysis Design and support event-driven analytics and real-time/streaming ML pipelines Collaborate with data engineers, architects, application teams, and SMEs to integrate AI/ML capabilities into enterprise systems and operational workflows Support system-of-systems (SoS) integrations across multiple systems, vendors, contractors, and interdependent platforms Establish AI governance frameworks supporting fairness, bias mitigation, explainability, transparency, and compliance with standards such as the NIST AI Risk Management Framework Develop reproducible analytics workflows, technical documentation, analysis plans, dashboards, and reporting deliverables Support DataOps and Agile data science practices including iterative development, pipeline automation, CI/CD integration, and collaborative model delivery Ensure analytics solutions align with enterprise security, privacy, and compliance requirements Drive improvements in data quality, validation, accessibility, and operational analytics reliability Present findings, recommendations, and technical approaches to executive leadership and stakeholders Mentor data scientists and analytics teams while promoting best practices across the organization Technical Environment Cloud-native AI/ML and analytics environments (AWS, Azure) Distributed data platforms and enterprise analytics ecosystems Python, R, Spark, TensorFlow, PyTorch, Databricks, and related ML frameworks MLOps pipelines, model deployment platforms, and automation frameworks Real-time streaming and event-driven analytics systems DevSecOps pipelines and CI/CD automation practices DataOps and Agile/SAFe delivery environments APIs, distributed integrations, and enterprise data platforms Collaboration and delivery tools (Git, Jira, Confluence) High-volume, near real-time processing environments What You Bring (Requirements) Baseline Requirements U.S. Citizenship with the ability to obtain a Public Trust PhD in Data Science, Computer Science, Statistics, Mathematics, or related field 15+ years of experience in data science, AI/ML, advanced analytics, or enterprise modernization initiatives Proven experience leading AI/ML and analytics efforts across large-scale, complex systems Ability to obtain and maintain a Public Trust clearance Technical Capabilities Deep expertise in machine learning, statistical modeling, and advanced analytics techniques Experience implementing end-to-end MLOps pipelines including model training, validation, deployment, monitoring, and scaling Experience with NLP, LLMs, deep learning, reinforcement learning, anomaly detection, and time series analytics Experience designing and supporting real-time or streaming analytics architectures Experience integrating AI/ML solutions across system-of-systems (SoS) environments and distributed enterprise platforms Experience implementing AI governance frameworks addressing explainability, fairness, transparency, and bias mitigation Experience with large-scale distributed data environments and cloud-native analytics platforms Experience with DataOps, CI/CD integration, and Agile/SAFe delivery models Strong experience with Python, R, Spark, TensorFlow, PyTorch, Databricks, and related AI/ML technologies Experience developing dashboards, technical reports, analysis plans, and reproducible analytics workflows Experience collaborating across engineering, architecture, application, and operational teams at enterprise scale Core Strengths Strong ownership mindset with accountability for enterprise AI/ML outcomes Ability to translate complex analytical findings into actionable business and mission insights Strategic thinker capable of balancing innovation, governance, and operational realities Effective communication across technical, operational, and executive stakeholders Strong leadership and mentoring capabilities across data science and analytics teams Ability to operate in complex, fast-moving, multi-contractor delivery environments Nice to Have (Differentiators) Experience supporting statistical and similarly large-scale federal modernization programs Experience implementing enterprise AI governance or responsible AI initiatives Experience with event-driven architectures, streaming analytics, or operational AI systems Experience supporting large-scale data modernization or enterprise analytics transformation efforts Experience working within DevSecOps-enabled AI/ML delivery environments _ Here at Revolutional we are pleased to have been repeatedly recognized for our outstanding work culture, the innovative work we do, and the employees on our team who make a difference each day. Some of these recognitions include: Recognized as a Top 20 "Best Place to Work in Virginia" Recipient of Department of Labor's HireVets Gold Medallion Great Place to Work Certification for five years running A Virginia Chamber of Commerce Fantastic 50 company A Northern Virginia Technology Council Tech 100 company Inc. 5000 list of fastest growing companies for eleven years Two-time SBA SBIR Tibbett's Award winner Virginia Values Veterans (V3) Certification We recognize that every bit of our success is the result of our teams of hard-working, motivated, and innovative professionals who are proud to call themselves part of the Revolutional family! In addition to competitive compensation, a family-focused culture, and a dynamic, productive work environment, we offer all full-time employees a variety of benefits including, but not limited to Traditional and HSA- eligible medical insurance plans 100% employer-paid dental and vision insurance options 100% employer-sponsored STD, LTD, and life insurance 5% 401(k) company matching Flexible-schedules and teleworking options Paid holidays and PTO Accrual Plans Paid Parental Leave Professional development and career growth opportunities Team and company-wide events, recognition, and appreciation and so much more! Check out our Revolutional LinkedIn to find out a little more about who we are and if we are the right next step for your career! Revolutional is an Equal Opportunity Employer providing equal employment opportunity to all employees and applicants for employment without regard to race, color, religion, national origin, age, gender . click apply for full job details
Job DescriptionJob DescriptionDescription: Lead Data Scientist At B&A, we foster and embrace a distinct set of values that we live by and instill in all aspects of our organization: dedication, commitment, partnership, trust, and recognition. We have incorporated these values into successful delivery for our customers since 1988. B&A believes in ensuring its employees feel deeply connected to B&A, recognizing successes and hard work, and providing continuous opportunities to learn and grow. Our people are entrepreneurial thinkers that combine mindset, vision, and experience to drive value - not only to us as an organization, but to the clients we support. We promote a collaborative culture with our clients, and with each other, as one team working towards a common vision. We'd love for you to join our team! Job Summary We are seeking a Subject Matter Expert (SME)-level Lead Data Scientist to leverage cutting-edge techniques to extract insights and patterns from large and complex datasets for the U.S. Census Bureau's Decennial Transformation and Application Modernization (DTAM) effort. This role provides technical and management leadership on major advanced data science assignments, developing advanced algorithms, models, and frameworks using machine learning, deep learning, natural language processing, and generative AI / large language models. The Lead Data Scientist ensures AI/ML products are safe, trustworthy, explainable, and compliant with the NIST AI Framework and Census Bureau policies. Decision-making and domain knowledge may have a critical impact on overall program implementation. May supervise others. Responsibilities Develop advanced algorithms, models, and frameworks leveraging machine learning, deep learning, neural networks, natural language processing, and generative AI / large language models (LLMs) Manage all activities to align with current advanced analytics and data science standards as defined by Decennial, the USCB, and industry best practices Support the transition of advanced analytics and data science capabilities from pilot to production and maintain them in the production environment Develop descriptive and predictive models for survey efforts, including time series, anomaly detection, semi-supervised, active, and reinforcement learning frameworks Conduct data cleaning, filtering, transformation, and feature engineering to create machine-learning-ready datasets Create, maintain, and use synthetic data to support the full lifecycle of advanced data science Follow AI regulation and ethical principles in accordance with the NIST AI Framework to manage AI risk and ensure model trustworthiness Ensure AI products are safe, secure, explainable, interpretable, privacy-enhanced, fair, valid, reliable, accountable, and transparent Develop, document, and test prototypes and proofs-of-concept leveraging advanced data science Evaluate trained models with multiple performance metrics, appropriate test sets, and learning curves Develop and maintain data science documentation, including analysis plans, technical reports, user manuals, and best-practice templates Education and Experience PhD in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field - mandatory 15+ years of experience providing technical and management leadership on major data science assignments (SME level) Required Skills Expert proficiency in Python, R, SAS, and SQL and associated data science libraries and tools Demonstrated experience developing and operationalizing ML, deep learning, NLP, and generative AI / LLM models Strong background in predictive modeling, time series analysis, anomaly detection, and feature engineering Experience creating and using synthetic data and privacy-preserving data techniques Working knowledge of the NIST AI Framework and responsible/ethical AI practices Desired Skills Experience transitioning data science capabilities from pilot to production (MLOps / LLMOps) Familiarity with differential privacy, federated learning, and secure multi-party computation Experience with large-scale federal statistical or survey data programs Excellent written and verbal communication skills, including manuscript preparation and executive briefing to senior Government stakeholders Security Clearance U.S. Citizenship required More About B&A: Notable Clients B&A has grown to be a company that is trusted by our clients for exceptional service, innovative solutions, and inspired employees. Our service extends through federal, state, and local Government, the private sector, and higher education. Some of our notable clients include Department of Homeland Security, U.S. Customs and Border Protection, U.S. Senate, U.S. Courts, U.S. Census Bureau, U.S. Navy, and more. Benefits and Programs B&A is proud to offer three robust individual and family medical plans to full time employees, including a Health Savings Account (HSA) option as well as two tiers of dental coverage, vision, life & AD&D, disability, accident, hospital indemnity, and critical illness insurance. In addition to these benefits, B&A employees enjoy paid time off, B&A sponsored trainings and certifications, pet insurance benefits, commuter transit benefits and a free subscription to a virtual exercise platform (NEOU). B&A's 401(k) plan is available to all employees and includes a company matching contribution. B&A has launched several programs to focus on employee engagement, wellness, and assistance. These include: The B&A Cares program: 30/60/90-day wellness check ins, personal development, financial management, and stress management seminars, and more A formal mentorship program Job shadowing and cross training opportunities Brand Ambassador program Employee Assistance Program (EAP) - Access to various support resources to include counseling, legal guidance, financial planning, and more Monthly teambuilding events B&A Annual Wellness Challenges: &A, &A, &A, &A, and more At B&A, we place significant importance on improving the communities and lives of citizens across the nation through our involvement, technology expertise, and employees. B&A puts an emphasis on charitable efforts in the Northern Virginia area, including Capital Area Food Bank pantry drives, book donations, Hope for Henry Foundation events, and many more. In recognition of all these efforts, B&A has been named a Companies as Responsive Employers (CARE) award recipient by Northern Virginia Family Services and nominated by the Northern Virginia Chamber of Commerce for Outstanding Corporate Citizenship Award. EEO B&A provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state and local laws. B&A complies with applicable state and local laws governing non-discrimination in employment in every location in which the company has facilities. This policy covers conduct occurring at B&A's offices, and other workplaces (including client sites) and all other locations where B&A is providing services, and to all work-related activities. EEO is the Law B&A participates in e-Verify. We provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 Form to confirm work authorization. Requirements:
06/08/2026
Full time
Job DescriptionJob DescriptionDescription: Lead Data Scientist At B&A, we foster and embrace a distinct set of values that we live by and instill in all aspects of our organization: dedication, commitment, partnership, trust, and recognition. We have incorporated these values into successful delivery for our customers since 1988. B&A believes in ensuring its employees feel deeply connected to B&A, recognizing successes and hard work, and providing continuous opportunities to learn and grow. Our people are entrepreneurial thinkers that combine mindset, vision, and experience to drive value - not only to us as an organization, but to the clients we support. We promote a collaborative culture with our clients, and with each other, as one team working towards a common vision. We'd love for you to join our team! Job Summary We are seeking a Subject Matter Expert (SME)-level Lead Data Scientist to leverage cutting-edge techniques to extract insights and patterns from large and complex datasets for the U.S. Census Bureau's Decennial Transformation and Application Modernization (DTAM) effort. This role provides technical and management leadership on major advanced data science assignments, developing advanced algorithms, models, and frameworks using machine learning, deep learning, natural language processing, and generative AI / large language models. The Lead Data Scientist ensures AI/ML products are safe, trustworthy, explainable, and compliant with the NIST AI Framework and Census Bureau policies. Decision-making and domain knowledge may have a critical impact on overall program implementation. May supervise others. Responsibilities Develop advanced algorithms, models, and frameworks leveraging machine learning, deep learning, neural networks, natural language processing, and generative AI / large language models (LLMs) Manage all activities to align with current advanced analytics and data science standards as defined by Decennial, the USCB, and industry best practices Support the transition of advanced analytics and data science capabilities from pilot to production and maintain them in the production environment Develop descriptive and predictive models for survey efforts, including time series, anomaly detection, semi-supervised, active, and reinforcement learning frameworks Conduct data cleaning, filtering, transformation, and feature engineering to create machine-learning-ready datasets Create, maintain, and use synthetic data to support the full lifecycle of advanced data science Follow AI regulation and ethical principles in accordance with the NIST AI Framework to manage AI risk and ensure model trustworthiness Ensure AI products are safe, secure, explainable, interpretable, privacy-enhanced, fair, valid, reliable, accountable, and transparent Develop, document, and test prototypes and proofs-of-concept leveraging advanced data science Evaluate trained models with multiple performance metrics, appropriate test sets, and learning curves Develop and maintain data science documentation, including analysis plans, technical reports, user manuals, and best-practice templates Education and Experience PhD in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field - mandatory 15+ years of experience providing technical and management leadership on major data science assignments (SME level) Required Skills Expert proficiency in Python, R, SAS, and SQL and associated data science libraries and tools Demonstrated experience developing and operationalizing ML, deep learning, NLP, and generative AI / LLM models Strong background in predictive modeling, time series analysis, anomaly detection, and feature engineering Experience creating and using synthetic data and privacy-preserving data techniques Working knowledge of the NIST AI Framework and responsible/ethical AI practices Desired Skills Experience transitioning data science capabilities from pilot to production (MLOps / LLMOps) Familiarity with differential privacy, federated learning, and secure multi-party computation Experience with large-scale federal statistical or survey data programs Excellent written and verbal communication skills, including manuscript preparation and executive briefing to senior Government stakeholders Security Clearance U.S. Citizenship required More About B&A: Notable Clients B&A has grown to be a company that is trusted by our clients for exceptional service, innovative solutions, and inspired employees. Our service extends through federal, state, and local Government, the private sector, and higher education. Some of our notable clients include Department of Homeland Security, U.S. Customs and Border Protection, U.S. Senate, U.S. Courts, U.S. Census Bureau, U.S. Navy, and more. Benefits and Programs B&A is proud to offer three robust individual and family medical plans to full time employees, including a Health Savings Account (HSA) option as well as two tiers of dental coverage, vision, life & AD&D, disability, accident, hospital indemnity, and critical illness insurance. In addition to these benefits, B&A employees enjoy paid time off, B&A sponsored trainings and certifications, pet insurance benefits, commuter transit benefits and a free subscription to a virtual exercise platform (NEOU). B&A's 401(k) plan is available to all employees and includes a company matching contribution. B&A has launched several programs to focus on employee engagement, wellness, and assistance. These include: The B&A Cares program: 30/60/90-day wellness check ins, personal development, financial management, and stress management seminars, and more A formal mentorship program Job shadowing and cross training opportunities Brand Ambassador program Employee Assistance Program (EAP) - Access to various support resources to include counseling, legal guidance, financial planning, and more Monthly teambuilding events B&A Annual Wellness Challenges: &A, &A, &A, &A, and more At B&A, we place significant importance on improving the communities and lives of citizens across the nation through our involvement, technology expertise, and employees. B&A puts an emphasis on charitable efforts in the Northern Virginia area, including Capital Area Food Bank pantry drives, book donations, Hope for Henry Foundation events, and many more. In recognition of all these efforts, B&A has been named a Companies as Responsive Employers (CARE) award recipient by Northern Virginia Family Services and nominated by the Northern Virginia Chamber of Commerce for Outstanding Corporate Citizenship Award. EEO B&A provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state and local laws. B&A complies with applicable state and local laws governing non-discrimination in employment in every location in which the company has facilities. This policy covers conduct occurring at B&A's offices, and other workplaces (including client sites) and all other locations where B&A is providing services, and to all work-related activities. EEO is the Law B&A participates in e-Verify. We provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 Form to confirm work authorization. Requirements:
Job DescriptionJob Description Opportunity Overview Northramp is seeking a Data Scientist to join the team supporting client's Cloud program - a mission-critical effort to consolidate, modernize, and operate client's enterprise cloud services across IaaS, PaaS, and SaaS environments under FedRAMP High authorization. You will develop analytical models, business intelligence solutions, and AI/ML capabilities that help client derive actionable insight from its enterprise data. The role spans statistical analysis, machine learning, and data visualization - with Looker as the primary BI delivery platform - in support of program operations, resource planning, and mission-critical decision-making. This role is part of Northramp's integrated delivery model, where engineers and advisors work as one team to bring sound judgment, disciplined execution, and deep federal experience to high-stakes modernization programs. Location & Work Arrangement Hybrid, based in the Washington, DC metro area. On-site presence at designated client locations is expected on a cadence aligned to program needs. Remote work is supported around mission and security requirements. This role is not open to candidates outside the DC region. The Ideal Candidate You turn data into decisions that program managers and agency leaders actually act on. You know when to reach for a simple statistical model and when the complexity of ML is actually warranted, and you've delivered BI solutions that get used rather than ignored. You communicate findings clearly to non-technical stakeholders and you operate with rigor around data quality and reproducibility. Key Responsibilities Design, develop, and maintain LookML data models, Looks, and Looker dashboards that deliver actionable business intelligence to client program stakeholders and leadership. Build and deploy machine learning models for classification, prediction, anomaly detection, and natural language processing use cases using Python (scikit-learn, TensorFlow, or PyTorch) and cloud AI/ML services (Vertex AI, SageMaker, or Azure ML). Conduct exploratory data analysis, statistical modeling, and hypothesis testing to surface patterns and insights in client operational and program data. Develop and maintain feature engineering pipelines, model training workflows, and model serving infrastructure integrated with cloud data platforms and BigQuery. Partner with Data Engineers to define data requirements, validate pipeline outputs, and ensure analytical datasets meet quality and completeness standards. Collaborate with program leadership and client government stakeholders to translate mission requirements into analytical problem definitions and measurable KPIs. Implement responsible AI practices - model explainability, bias assessment, and documentation standards - consistent with federal AI governance frameworks. Build and maintain automated reporting and alerting workflows that surface operational metrics and anomalies to the right stakeholders at the right time. Document data science methodologies, model assumptions, validation results, and performance metrics to support ATO and audit requirements. Mentor junior analysts and support adoption of data-driven practices across the delivery team. Requirements Required Qualifications 3 to 6 years of progressive, hands-on experience in data science or applied analytics with production model deployment experience. Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field. Proficiency in Python for data science (pandas, NumPy, scikit-learn, statsmodels) and SQL for data extraction and analysis. Hands-on experience with Looker - LookML modeling, dashboard development, and content management. Experience training, validating, and deploying machine learning models in cloud environments (Vertex AI, SageMaker, or Azure ML). Strong grounding in statistical methods: regression, classification, time series analysis, and A/B testing. Working knowledge of BigQuery or equivalent cloud data warehouses for large-scale analytical workloads. Experience with data visualization best practices and BI tooling beyond Looker (e.g., Tableau, Power BI, or Google Looker Studio). Familiarity with MLOps principles: model versioning, experiment tracking (MLflow or Vertex AI Experiments), and deployment pipelines. Understanding of federal AI governance guidance (OMB M-24-10 or equivalent) and FedRAMP data handling requirements. U.S. Citizenship and the ability to obtain and maintain a DHS suitability / Public Trust clearance. Desired Qualifications Google Cloud Professional Machine Learning Engineer or equivalent AWS/Azure ML certification. Looker certification or demonstrated advanced LookML experience. Security+ or equivalent certification. Experience with NLP, computer vision, or generative AI application development. Federal data science or analytics program experience. Active Public Trust or higher clearance. Clearance DHS suitability and a Public Trust background investigation are required for this role. Active Public Trust or higher clearance is preferred. Selected applicants will be subject to a security investigation and may need to meet eligibility requirements for access to controlled or classified information. About Northramp Northramp is a federal consulting firm that helps agencies modernize and operate mission-critical systems with sound judgment, disciplined execution, and deep federal experience. We specialize in high-stakes digital transformation in highly regulated environments where failure is not an option. Our integrated delivery model brings engineers and advisors together as one team, combining technical depth with an operator's mindset to move organizations from strategy to execution with confidence. We hold high standards because our clients' missions demand it, and we support our people in meeting them. Northramp is where you are challenged, trusted, and supported - a place for people who take pride in their work, value clarity and follow-through, and want to make a meaningful impact through technology. Equal Opportunity Northramp is an Equal Opportunity Employer. We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by federal, state, or local law. Northramp participates in E-Verify. Benefits Health Care Plan (Medical, Dental & Vision) Retirement Plan (401k, IRA) Life Insurance (Basic, Voluntary & AD&D) Paid Time Off (Vacation, Sick & Public Holidays) Family Leave (Maternity, Paternity) Short Term & Long Term Disability Training & Development Work From Home Wellness Resources Employee Bonus Programs
06/08/2026
Full time
Job DescriptionJob Description Opportunity Overview Northramp is seeking a Data Scientist to join the team supporting client's Cloud program - a mission-critical effort to consolidate, modernize, and operate client's enterprise cloud services across IaaS, PaaS, and SaaS environments under FedRAMP High authorization. You will develop analytical models, business intelligence solutions, and AI/ML capabilities that help client derive actionable insight from its enterprise data. The role spans statistical analysis, machine learning, and data visualization - with Looker as the primary BI delivery platform - in support of program operations, resource planning, and mission-critical decision-making. This role is part of Northramp's integrated delivery model, where engineers and advisors work as one team to bring sound judgment, disciplined execution, and deep federal experience to high-stakes modernization programs. Location & Work Arrangement Hybrid, based in the Washington, DC metro area. On-site presence at designated client locations is expected on a cadence aligned to program needs. Remote work is supported around mission and security requirements. This role is not open to candidates outside the DC region. The Ideal Candidate You turn data into decisions that program managers and agency leaders actually act on. You know when to reach for a simple statistical model and when the complexity of ML is actually warranted, and you've delivered BI solutions that get used rather than ignored. You communicate findings clearly to non-technical stakeholders and you operate with rigor around data quality and reproducibility. Key Responsibilities Design, develop, and maintain LookML data models, Looks, and Looker dashboards that deliver actionable business intelligence to client program stakeholders and leadership. Build and deploy machine learning models for classification, prediction, anomaly detection, and natural language processing use cases using Python (scikit-learn, TensorFlow, or PyTorch) and cloud AI/ML services (Vertex AI, SageMaker, or Azure ML). Conduct exploratory data analysis, statistical modeling, and hypothesis testing to surface patterns and insights in client operational and program data. Develop and maintain feature engineering pipelines, model training workflows, and model serving infrastructure integrated with cloud data platforms and BigQuery. Partner with Data Engineers to define data requirements, validate pipeline outputs, and ensure analytical datasets meet quality and completeness standards. Collaborate with program leadership and client government stakeholders to translate mission requirements into analytical problem definitions and measurable KPIs. Implement responsible AI practices - model explainability, bias assessment, and documentation standards - consistent with federal AI governance frameworks. Build and maintain automated reporting and alerting workflows that surface operational metrics and anomalies to the right stakeholders at the right time. Document data science methodologies, model assumptions, validation results, and performance metrics to support ATO and audit requirements. Mentor junior analysts and support adoption of data-driven practices across the delivery team. Requirements Required Qualifications 3 to 6 years of progressive, hands-on experience in data science or applied analytics with production model deployment experience. Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field. Proficiency in Python for data science (pandas, NumPy, scikit-learn, statsmodels) and SQL for data extraction and analysis. Hands-on experience with Looker - LookML modeling, dashboard development, and content management. Experience training, validating, and deploying machine learning models in cloud environments (Vertex AI, SageMaker, or Azure ML). Strong grounding in statistical methods: regression, classification, time series analysis, and A/B testing. Working knowledge of BigQuery or equivalent cloud data warehouses for large-scale analytical workloads. Experience with data visualization best practices and BI tooling beyond Looker (e.g., Tableau, Power BI, or Google Looker Studio). Familiarity with MLOps principles: model versioning, experiment tracking (MLflow or Vertex AI Experiments), and deployment pipelines. Understanding of federal AI governance guidance (OMB M-24-10 or equivalent) and FedRAMP data handling requirements. U.S. Citizenship and the ability to obtain and maintain a DHS suitability / Public Trust clearance. Desired Qualifications Google Cloud Professional Machine Learning Engineer or equivalent AWS/Azure ML certification. Looker certification or demonstrated advanced LookML experience. Security+ or equivalent certification. Experience with NLP, computer vision, or generative AI application development. Federal data science or analytics program experience. Active Public Trust or higher clearance. Clearance DHS suitability and a Public Trust background investigation are required for this role. Active Public Trust or higher clearance is preferred. Selected applicants will be subject to a security investigation and may need to meet eligibility requirements for access to controlled or classified information. About Northramp Northramp is a federal consulting firm that helps agencies modernize and operate mission-critical systems with sound judgment, disciplined execution, and deep federal experience. We specialize in high-stakes digital transformation in highly regulated environments where failure is not an option. Our integrated delivery model brings engineers and advisors together as one team, combining technical depth with an operator's mindset to move organizations from strategy to execution with confidence. We hold high standards because our clients' missions demand it, and we support our people in meeting them. Northramp is where you are challenged, trusted, and supported - a place for people who take pride in their work, value clarity and follow-through, and want to make a meaningful impact through technology. Equal Opportunity Northramp is an Equal Opportunity Employer. We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by federal, state, or local law. Northramp participates in E-Verify. Benefits Health Care Plan (Medical, Dental & Vision) Retirement Plan (401k, IRA) Life Insurance (Basic, Voluntary & AD&D) Paid Time Off (Vacation, Sick & Public Holidays) Family Leave (Maternity, Paternity) Short Term & Long Term Disability Training & Development Work From Home Wellness Resources Employee Bonus Programs
Job DescriptionJob Description Opportunity Overview Northramp is seeking a Data Scientist to join the team supporting client's Cloud program - a mission-critical effort to consolidate, modernize, and operate client's enterprise cloud services across IaaS, PaaS, and SaaS environments under FedRAMP High authorization. You will develop analytical models, business intelligence solutions, and AI/ML capabilities that help client derive actionable insight from its enterprise data. The role spans statistical analysis, machine learning, and data visualization - with Looker as the primary BI delivery platform - in support of program operations, resource planning, and mission-critical decision-making. This role is part of Northramp's integrated delivery model, where engineers and advisors work as one team to bring sound judgment, disciplined execution, and deep federal experience to high-stakes modernization programs. Location & Work Arrangement Hybrid, based in the Washington, DC metro area. On-site presence at designated client locations is expected on a cadence aligned to program needs. Remote work is supported around mission and security requirements. This role is not open to candidates outside the DC region. The Ideal Candidate You turn data into decisions that program managers and agency leaders actually act on. You know when to reach for a simple statistical model and when the complexity of ML is actually warranted, and you've delivered BI solutions that get used rather than ignored. You communicate findings clearly to non-technical stakeholders and you operate with rigor around data quality and reproducibility. Key Responsibilities Design, develop, and maintain LookML data models, Looks, and Looker dashboards that deliver actionable business intelligence to client program stakeholders and leadership. Build and deploy machine learning models for classification, prediction, anomaly detection, and natural language processing use cases using Python (scikit-learn, TensorFlow, or PyTorch) and cloud AI/ML services (Vertex AI, SageMaker, or Azure ML). Conduct exploratory data analysis, statistical modeling, and hypothesis testing to surface patterns and insights in client operational and program data. Develop and maintain feature engineering pipelines, model training workflows, and model serving infrastructure integrated with cloud data platforms and BigQuery. Partner with Data Engineers to define data requirements, validate pipeline outputs, and ensure analytical datasets meet quality and completeness standards. Collaborate with program leadership and client government stakeholders to translate mission requirements into analytical problem definitions and measurable KPIs. Implement responsible AI practices - model explainability, bias assessment, and documentation standards - consistent with federal AI governance frameworks. Build and maintain automated reporting and alerting workflows that surface operational metrics and anomalies to the right stakeholders at the right time. Document data science methodologies, model assumptions, validation results, and performance metrics to support ATO and audit requirements. Mentor junior analysts and support adoption of data-driven practices across the delivery team. Requirements Required Qualifications 3 to 6 years of progressive, hands-on experience in data science or applied analytics with production model deployment experience. Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field. Proficiency in Python for data science (pandas, NumPy, scikit-learn, statsmodels) and SQL for data extraction and analysis. Hands-on experience with Looker - LookML modeling, dashboard development, and content management. Experience training, validating, and deploying machine learning models in cloud environments (Vertex AI, SageMaker, or Azure ML). Strong grounding in statistical methods: regression, classification, time series analysis, and A/B testing. Working knowledge of BigQuery or equivalent cloud data warehouses for large-scale analytical workloads. Experience with data visualization best practices and BI tooling beyond Looker (e.g., Tableau, Power BI, or Google Looker Studio). Familiarity with MLOps principles: model versioning, experiment tracking (MLflow or Vertex AI Experiments), and deployment pipelines. Understanding of federal AI governance guidance (OMB M-24-10 or equivalent) and FedRAMP data handling requirements. U.S. Citizenship and the ability to obtain and maintain a DHS suitability / Public Trust clearance. Desired Qualifications Google Cloud Professional Machine Learning Engineer or equivalent AWS/Azure ML certification. Looker certification or demonstrated advanced LookML experience. Security+ or equivalent certification. Experience with NLP, computer vision, or generative AI application development. Federal data science or analytics program experience. Active Public Trust or higher clearance. Clearance DHS suitability and a Public Trust background investigation are required for this role. Active Public Trust or higher clearance is preferred. Selected applicants will be subject to a security investigation and may need to meet eligibility requirements for access to controlled or classified information. About Northramp Northramp is a federal consulting firm that helps agencies modernize and operate mission-critical systems with sound judgment, disciplined execution, and deep federal experience. We specialize in high-stakes digital transformation in highly regulated environments where failure is not an option. Our integrated delivery model brings engineers and advisors together as one team, combining technical depth with an operator's mindset to move organizations from strategy to execution with confidence. We hold high standards because our clients' missions demand it, and we support our people in meeting them. Northramp is where you are challenged, trusted, and supported - a place for people who take pride in their work, value clarity and follow-through, and want to make a meaningful impact through technology. Equal Opportunity Northramp is an Equal Opportunity Employer. We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by federal, state, or local law. Northramp participates in E-Verify. Benefits Health Care Plan (Medical, Dental & Vision) Retirement Plan (401k, IRA) Life Insurance (Basic, Voluntary & AD&D) Paid Time Off (Vacation, Sick & Public Holidays) Family Leave (Maternity, Paternity) Short Term & Long Term Disability Training & Development Work From Home Wellness Resources Employee Bonus Programs
06/08/2026
Full time
Job DescriptionJob Description Opportunity Overview Northramp is seeking a Data Scientist to join the team supporting client's Cloud program - a mission-critical effort to consolidate, modernize, and operate client's enterprise cloud services across IaaS, PaaS, and SaaS environments under FedRAMP High authorization. You will develop analytical models, business intelligence solutions, and AI/ML capabilities that help client derive actionable insight from its enterprise data. The role spans statistical analysis, machine learning, and data visualization - with Looker as the primary BI delivery platform - in support of program operations, resource planning, and mission-critical decision-making. This role is part of Northramp's integrated delivery model, where engineers and advisors work as one team to bring sound judgment, disciplined execution, and deep federal experience to high-stakes modernization programs. Location & Work Arrangement Hybrid, based in the Washington, DC metro area. On-site presence at designated client locations is expected on a cadence aligned to program needs. Remote work is supported around mission and security requirements. This role is not open to candidates outside the DC region. The Ideal Candidate You turn data into decisions that program managers and agency leaders actually act on. You know when to reach for a simple statistical model and when the complexity of ML is actually warranted, and you've delivered BI solutions that get used rather than ignored. You communicate findings clearly to non-technical stakeholders and you operate with rigor around data quality and reproducibility. Key Responsibilities Design, develop, and maintain LookML data models, Looks, and Looker dashboards that deliver actionable business intelligence to client program stakeholders and leadership. Build and deploy machine learning models for classification, prediction, anomaly detection, and natural language processing use cases using Python (scikit-learn, TensorFlow, or PyTorch) and cloud AI/ML services (Vertex AI, SageMaker, or Azure ML). Conduct exploratory data analysis, statistical modeling, and hypothesis testing to surface patterns and insights in client operational and program data. Develop and maintain feature engineering pipelines, model training workflows, and model serving infrastructure integrated with cloud data platforms and BigQuery. Partner with Data Engineers to define data requirements, validate pipeline outputs, and ensure analytical datasets meet quality and completeness standards. Collaborate with program leadership and client government stakeholders to translate mission requirements into analytical problem definitions and measurable KPIs. Implement responsible AI practices - model explainability, bias assessment, and documentation standards - consistent with federal AI governance frameworks. Build and maintain automated reporting and alerting workflows that surface operational metrics and anomalies to the right stakeholders at the right time. Document data science methodologies, model assumptions, validation results, and performance metrics to support ATO and audit requirements. Mentor junior analysts and support adoption of data-driven practices across the delivery team. Requirements Required Qualifications 3 to 6 years of progressive, hands-on experience in data science or applied analytics with production model deployment experience. Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field. Proficiency in Python for data science (pandas, NumPy, scikit-learn, statsmodels) and SQL for data extraction and analysis. Hands-on experience with Looker - LookML modeling, dashboard development, and content management. Experience training, validating, and deploying machine learning models in cloud environments (Vertex AI, SageMaker, or Azure ML). Strong grounding in statistical methods: regression, classification, time series analysis, and A/B testing. Working knowledge of BigQuery or equivalent cloud data warehouses for large-scale analytical workloads. Experience with data visualization best practices and BI tooling beyond Looker (e.g., Tableau, Power BI, or Google Looker Studio). Familiarity with MLOps principles: model versioning, experiment tracking (MLflow or Vertex AI Experiments), and deployment pipelines. Understanding of federal AI governance guidance (OMB M-24-10 or equivalent) and FedRAMP data handling requirements. U.S. Citizenship and the ability to obtain and maintain a DHS suitability / Public Trust clearance. Desired Qualifications Google Cloud Professional Machine Learning Engineer or equivalent AWS/Azure ML certification. Looker certification or demonstrated advanced LookML experience. Security+ or equivalent certification. Experience with NLP, computer vision, or generative AI application development. Federal data science or analytics program experience. Active Public Trust or higher clearance. Clearance DHS suitability and a Public Trust background investigation are required for this role. Active Public Trust or higher clearance is preferred. Selected applicants will be subject to a security investigation and may need to meet eligibility requirements for access to controlled or classified information. About Northramp Northramp is a federal consulting firm that helps agencies modernize and operate mission-critical systems with sound judgment, disciplined execution, and deep federal experience. We specialize in high-stakes digital transformation in highly regulated environments where failure is not an option. Our integrated delivery model brings engineers and advisors together as one team, combining technical depth with an operator's mindset to move organizations from strategy to execution with confidence. We hold high standards because our clients' missions demand it, and we support our people in meeting them. Northramp is where you are challenged, trusted, and supported - a place for people who take pride in their work, value clarity and follow-through, and want to make a meaningful impact through technology. Equal Opportunity Northramp is an Equal Opportunity Employer. We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by federal, state, or local law. Northramp participates in E-Verify. Benefits Health Care Plan (Medical, Dental & Vision) Retirement Plan (401k, IRA) Life Insurance (Basic, Voluntary & AD&D) Paid Time Off (Vacation, Sick & Public Holidays) Family Leave (Maternity, Paternity) Short Term & Long Term Disability Training & Development Work From Home Wellness Resources Employee Bonus Programs
Job DescriptionJob DescriptionDescription: Lead Data Scientist At B&A, we foster and embrace a distinct set of values that we live by and instill in all aspects of our organization: dedication, commitment, partnership, trust, and recognition. We have incorporated these values into successful delivery for our customers since 1988. B&A believes in ensuring its employees feel deeply connected to B&A, recognizing successes and hard work, and providing continuous opportunities to learn and grow. Our people are entrepreneurial thinkers that combine mindset, vision, and experience to drive value - not only to us as an organization, but to the clients we support. We promote a collaborative culture with our clients, and with each other, as one team working towards a common vision. We'd love for you to join our team! Job Summary We are seeking a Subject Matter Expert (SME)-level Lead Data Scientist to leverage cutting-edge techniques to extract insights and patterns from large and complex datasets for the U.S. Census Bureau's Decennial Transformation and Application Modernization (DTAM) effort. This role provides technical and management leadership on major advanced data science assignments, developing advanced algorithms, models, and frameworks using machine learning, deep learning, natural language processing, and generative AI / large language models. The Lead Data Scientist ensures AI/ML products are safe, trustworthy, explainable, and compliant with the NIST AI Framework and Census Bureau policies. Decision-making and domain knowledge may have a critical impact on overall program implementation. May supervise others. Responsibilities Develop advanced algorithms, models, and frameworks leveraging machine learning, deep learning, neural networks, natural language processing, and generative AI / large language models (LLMs) Manage all activities to align with current advanced analytics and data science standards as defined by Decennial, the USCB, and industry best practices Support the transition of advanced analytics and data science capabilities from pilot to production and maintain them in the production environment Develop descriptive and predictive models for survey efforts, including time series, anomaly detection, semi-supervised, active, and reinforcement learning frameworks Conduct data cleaning, filtering, transformation, and feature engineering to create machine-learning-ready datasets Create, maintain, and use synthetic data to support the full lifecycle of advanced data science Follow AI regulation and ethical principles in accordance with the NIST AI Framework to manage AI risk and ensure model trustworthiness Ensure AI products are safe, secure, explainable, interpretable, privacy-enhanced, fair, valid, reliable, accountable, and transparent Develop, document, and test prototypes and proofs-of-concept leveraging advanced data science Evaluate trained models with multiple performance metrics, appropriate test sets, and learning curves Develop and maintain data science documentation, including analysis plans, technical reports, user manuals, and best-practice templates Education and Experience PhD in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field - mandatory 15+ years of experience providing technical and management leadership on major data science assignments (SME level) Required Skills Expert proficiency in Python, R, SAS, and SQL and associated data science libraries and tools Demonstrated experience developing and operationalizing ML, deep learning, NLP, and generative AI / LLM models Strong background in predictive modeling, time series analysis, anomaly detection, and feature engineering Experience creating and using synthetic data and privacy-preserving data techniques Working knowledge of the NIST AI Framework and responsible/ethical AI practices Desired Skills Experience transitioning data science capabilities from pilot to production (MLOps / LLMOps) Familiarity with differential privacy, federated learning, and secure multi-party computation Experience with large-scale federal statistical or survey data programs Excellent written and verbal communication skills, including manuscript preparation and executive briefing to senior Government stakeholders Security Clearance U.S. Citizenship required More About B&A: Notable Clients B&A has grown to be a company that is trusted by our clients for exceptional service, innovative solutions, and inspired employees. Our service extends through federal, state, and local Government, the private sector, and higher education. Some of our notable clients include Department of Homeland Security, U.S. Customs and Border Protection, U.S. Senate, U.S. Courts, U.S. Census Bureau, U.S. Navy, and more. Benefits and Programs B&A is proud to offer three robust individual and family medical plans to full time employees, including a Health Savings Account (HSA) option as well as two tiers of dental coverage, vision, life & AD&D, disability, accident, hospital indemnity, and critical illness insurance. In addition to these benefits, B&A employees enjoy paid time off, B&A sponsored trainings and certifications, pet insurance benefits, commuter transit benefits and a free subscription to a virtual exercise platform (NEOU). B&A's 401(k) plan is available to all employees and includes a company matching contribution. B&A has launched several programs to focus on employee engagement, wellness, and assistance. These include: The B&A Cares program: 30/60/90-day wellness check ins, personal development, financial management, and stress management seminars, and more A formal mentorship program Job shadowing and cross training opportunities Brand Ambassador program Employee Assistance Program (EAP) - Access to various support resources to include counseling, legal guidance, financial planning, and more Monthly teambuilding events B&A Annual Wellness Challenges: &A, &A, &A, &A, and more At B&A, we place significant importance on improving the communities and lives of citizens across the nation through our involvement, technology expertise, and employees. B&A puts an emphasis on charitable efforts in the Northern Virginia area, including Capital Area Food Bank pantry drives, book donations, Hope for Henry Foundation events, and many more. In recognition of all these efforts, B&A has been named a Companies as Responsive Employers (CARE) award recipient by Northern Virginia Family Services and nominated by the Northern Virginia Chamber of Commerce for Outstanding Corporate Citizenship Award. EEO B&A provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state and local laws. B&A complies with applicable state and local laws governing non-discrimination in employment in every location in which the company has facilities. This policy covers conduct occurring at B&A's offices, and other workplaces (including client sites) and all other locations where B&A is providing services, and to all work-related activities. EEO is the Law B&A participates in e-Verify. We provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 Form to confirm work authorization. Requirements:
06/08/2026
Full time
Job DescriptionJob DescriptionDescription: Lead Data Scientist At B&A, we foster and embrace a distinct set of values that we live by and instill in all aspects of our organization: dedication, commitment, partnership, trust, and recognition. We have incorporated these values into successful delivery for our customers since 1988. B&A believes in ensuring its employees feel deeply connected to B&A, recognizing successes and hard work, and providing continuous opportunities to learn and grow. Our people are entrepreneurial thinkers that combine mindset, vision, and experience to drive value - not only to us as an organization, but to the clients we support. We promote a collaborative culture with our clients, and with each other, as one team working towards a common vision. We'd love for you to join our team! Job Summary We are seeking a Subject Matter Expert (SME)-level Lead Data Scientist to leverage cutting-edge techniques to extract insights and patterns from large and complex datasets for the U.S. Census Bureau's Decennial Transformation and Application Modernization (DTAM) effort. This role provides technical and management leadership on major advanced data science assignments, developing advanced algorithms, models, and frameworks using machine learning, deep learning, natural language processing, and generative AI / large language models. The Lead Data Scientist ensures AI/ML products are safe, trustworthy, explainable, and compliant with the NIST AI Framework and Census Bureau policies. Decision-making and domain knowledge may have a critical impact on overall program implementation. May supervise others. Responsibilities Develop advanced algorithms, models, and frameworks leveraging machine learning, deep learning, neural networks, natural language processing, and generative AI / large language models (LLMs) Manage all activities to align with current advanced analytics and data science standards as defined by Decennial, the USCB, and industry best practices Support the transition of advanced analytics and data science capabilities from pilot to production and maintain them in the production environment Develop descriptive and predictive models for survey efforts, including time series, anomaly detection, semi-supervised, active, and reinforcement learning frameworks Conduct data cleaning, filtering, transformation, and feature engineering to create machine-learning-ready datasets Create, maintain, and use synthetic data to support the full lifecycle of advanced data science Follow AI regulation and ethical principles in accordance with the NIST AI Framework to manage AI risk and ensure model trustworthiness Ensure AI products are safe, secure, explainable, interpretable, privacy-enhanced, fair, valid, reliable, accountable, and transparent Develop, document, and test prototypes and proofs-of-concept leveraging advanced data science Evaluate trained models with multiple performance metrics, appropriate test sets, and learning curves Develop and maintain data science documentation, including analysis plans, technical reports, user manuals, and best-practice templates Education and Experience PhD in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field - mandatory 15+ years of experience providing technical and management leadership on major data science assignments (SME level) Required Skills Expert proficiency in Python, R, SAS, and SQL and associated data science libraries and tools Demonstrated experience developing and operationalizing ML, deep learning, NLP, and generative AI / LLM models Strong background in predictive modeling, time series analysis, anomaly detection, and feature engineering Experience creating and using synthetic data and privacy-preserving data techniques Working knowledge of the NIST AI Framework and responsible/ethical AI practices Desired Skills Experience transitioning data science capabilities from pilot to production (MLOps / LLMOps) Familiarity with differential privacy, federated learning, and secure multi-party computation Experience with large-scale federal statistical or survey data programs Excellent written and verbal communication skills, including manuscript preparation and executive briefing to senior Government stakeholders Security Clearance U.S. Citizenship required More About B&A: Notable Clients B&A has grown to be a company that is trusted by our clients for exceptional service, innovative solutions, and inspired employees. Our service extends through federal, state, and local Government, the private sector, and higher education. Some of our notable clients include Department of Homeland Security, U.S. Customs and Border Protection, U.S. Senate, U.S. Courts, U.S. Census Bureau, U.S. Navy, and more. Benefits and Programs B&A is proud to offer three robust individual and family medical plans to full time employees, including a Health Savings Account (HSA) option as well as two tiers of dental coverage, vision, life & AD&D, disability, accident, hospital indemnity, and critical illness insurance. In addition to these benefits, B&A employees enjoy paid time off, B&A sponsored trainings and certifications, pet insurance benefits, commuter transit benefits and a free subscription to a virtual exercise platform (NEOU). B&A's 401(k) plan is available to all employees and includes a company matching contribution. B&A has launched several programs to focus on employee engagement, wellness, and assistance. These include: The B&A Cares program: 30/60/90-day wellness check ins, personal development, financial management, and stress management seminars, and more A formal mentorship program Job shadowing and cross training opportunities Brand Ambassador program Employee Assistance Program (EAP) - Access to various support resources to include counseling, legal guidance, financial planning, and more Monthly teambuilding events B&A Annual Wellness Challenges: &A, &A, &A, &A, and more At B&A, we place significant importance on improving the communities and lives of citizens across the nation through our involvement, technology expertise, and employees. B&A puts an emphasis on charitable efforts in the Northern Virginia area, including Capital Area Food Bank pantry drives, book donations, Hope for Henry Foundation events, and many more. In recognition of all these efforts, B&A has been named a Companies as Responsive Employers (CARE) award recipient by Northern Virginia Family Services and nominated by the Northern Virginia Chamber of Commerce for Outstanding Corporate Citizenship Award. EEO B&A provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state and local laws. B&A complies with applicable state and local laws governing non-discrimination in employment in every location in which the company has facilities. This policy covers conduct occurring at B&A's offices, and other workplaces (including client sites) and all other locations where B&A is providing services, and to all work-related activities. EEO is the Law B&A participates in e-Verify. We provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 Form to confirm work authorization. Requirements:
Job DescriptionJob Description CTEC is a leading technology firm that provides modernization, digital transformation, and application development services to the U.S. Federal Government. Headquartered in McLean, VA, CTEC has over 300 team members working on mission-critical systems and projects for agencies such as the Department of Homeland Security, Internal Revenue Service, and the Office of Personnel Management. The work we do effects millions of U.S. citizens daily as they interact with the systems we build. Our best-in-class commercial solutions, modified for our customers' bespoke mission requirements, are enabling this future every day. The Company has experienced rapid growth over the past 3 years and recently received a strategic investment from Main Street Capital Corporation (NYSE: MAIN). In addition to our recent growth in Federal Civilian agencies, we are seeking to expand our capabilities in cloud development and footprint in national-security focused agencies within the Department of Defense and U.S. Intelligence Community. We are seeking to hire a AI/Machine Learning Engineer to our team! Role Overview: As an AI/ML Engineer for CTEC, you will develop Agentic AI systems designed to automate and optimize health benefits determinations for the Office of Personnel Management (OPM). Unlike traditional "black-box" models, your work will focus on marrying the reasoning capabilities of Large Language Models (LLMs) with deterministic, rule-driven patterns to ensure accuracy, auditability, and compliance in complex decision-making workflows. Duties and Responsibilities: Agentic System Architecture: Design and deploy autonomous AI agents capable of multi-step reasoning, tool-use, and self-correction to navigate complex federal benefit policies. Deterministic Logic Integration: Develop "Guardrail" layers that synchronize probabilistic LLM outputs with rigid business rules, ensuring benefit determinations adhere strictly to legal and regulatory frameworks. RAG & Knowledge Engineering: Implement advanced Retrieval-Augmented Generation (RAG) solutions, utilizing layout-aware parsing to extract information from dense manuals/documentation and unstructured data. Hybrid Model Development: Design and evaluate machine learning models that support both data-driven predictions and symbolic/rule-based automation. MLOps & Agent Monitoring: Deploy models into cloud environments with a focus on LLM-specific observability (tracing reasoning loops, monitoring for hallucinations, and detecting data drift in logic). Auditability & Explainability: Ensure every AI-driven determination has a clear, human-readable "audit trail" or reasoning chain that justifies the outcome based on source documentation. Collaboration: Work alongside solution architects and business stakeholders to translate complex health insurance policies into executable AI logic. Skills & Work Experience: Professional Experience: 5+ years in Machine Learning or Data Science, with at least 2 years of hands-on experience with LLM orchestration and Generative AI frameworks. Agentic Frameworks: Proficiency with tools such as LangChain, LangGraph, CrewAI, or Semantic Kernel for building multi-step agent workflows. Core Development: Strong proficiency in Python and experience with standard frameworks (PyTorch, TensorFlow, or Scikit-learn) Data Engineering: Strong SQL skills and experience with distributed data processing (Spark/PySpark) to handle large-scale enterprise data. Analytical Rigor: Ability to debug non-deterministic systems and implement rigorous evaluation frameworks (e.g., RAGAS, LLM-as-a-judge) data platforms. Preferred: Experience with Azure Machine Learning, Azure AI services, or similar cloud AI platforms. Experience implementing Generative AI, LLM, or RAG-based solutions. Experience supporting federal IT modernization or data transformation programs. Familiarity with healthcare, insurance, or benefits administration data environments. Experience applying data governance, privacy, and security best practices in AI/ML solutions. Education: Bachelor's degree in Computer Science, Data Science, Engineering, or a related discipline. Master's degree preferred. Equivalent professional experience will be considered in lieu of a degree. Clearance: Must be a U.S. citizen and be able to obtain an OPM Public Trust clearance. If you are looking for a fun and challenging environment with talented, motivated people to work with, CTEC is the right place for you. In addition to employee salary, we offer an array of employee benefits including: Paid vacation & Sick leave Health insurance coverage Career training Performance bonus programs 401K contribution & Employer Match 11 Federal Holidays
06/08/2026
Full time
Job DescriptionJob Description CTEC is a leading technology firm that provides modernization, digital transformation, and application development services to the U.S. Federal Government. Headquartered in McLean, VA, CTEC has over 300 team members working on mission-critical systems and projects for agencies such as the Department of Homeland Security, Internal Revenue Service, and the Office of Personnel Management. The work we do effects millions of U.S. citizens daily as they interact with the systems we build. Our best-in-class commercial solutions, modified for our customers' bespoke mission requirements, are enabling this future every day. The Company has experienced rapid growth over the past 3 years and recently received a strategic investment from Main Street Capital Corporation (NYSE: MAIN). In addition to our recent growth in Federal Civilian agencies, we are seeking to expand our capabilities in cloud development and footprint in national-security focused agencies within the Department of Defense and U.S. Intelligence Community. We are seeking to hire a AI/Machine Learning Engineer to our team! Role Overview: As an AI/ML Engineer for CTEC, you will develop Agentic AI systems designed to automate and optimize health benefits determinations for the Office of Personnel Management (OPM). Unlike traditional "black-box" models, your work will focus on marrying the reasoning capabilities of Large Language Models (LLMs) with deterministic, rule-driven patterns to ensure accuracy, auditability, and compliance in complex decision-making workflows. Duties and Responsibilities: Agentic System Architecture: Design and deploy autonomous AI agents capable of multi-step reasoning, tool-use, and self-correction to navigate complex federal benefit policies. Deterministic Logic Integration: Develop "Guardrail" layers that synchronize probabilistic LLM outputs with rigid business rules, ensuring benefit determinations adhere strictly to legal and regulatory frameworks. RAG & Knowledge Engineering: Implement advanced Retrieval-Augmented Generation (RAG) solutions, utilizing layout-aware parsing to extract information from dense manuals/documentation and unstructured data. Hybrid Model Development: Design and evaluate machine learning models that support both data-driven predictions and symbolic/rule-based automation. MLOps & Agent Monitoring: Deploy models into cloud environments with a focus on LLM-specific observability (tracing reasoning loops, monitoring for hallucinations, and detecting data drift in logic). Auditability & Explainability: Ensure every AI-driven determination has a clear, human-readable "audit trail" or reasoning chain that justifies the outcome based on source documentation. Collaboration: Work alongside solution architects and business stakeholders to translate complex health insurance policies into executable AI logic. Skills & Work Experience: Professional Experience: 5+ years in Machine Learning or Data Science, with at least 2 years of hands-on experience with LLM orchestration and Generative AI frameworks. Agentic Frameworks: Proficiency with tools such as LangChain, LangGraph, CrewAI, or Semantic Kernel for building multi-step agent workflows. Core Development: Strong proficiency in Python and experience with standard frameworks (PyTorch, TensorFlow, or Scikit-learn) Data Engineering: Strong SQL skills and experience with distributed data processing (Spark/PySpark) to handle large-scale enterprise data. Analytical Rigor: Ability to debug non-deterministic systems and implement rigorous evaluation frameworks (e.g., RAGAS, LLM-as-a-judge) data platforms. Preferred: Experience with Azure Machine Learning, Azure AI services, or similar cloud AI platforms. Experience implementing Generative AI, LLM, or RAG-based solutions. Experience supporting federal IT modernization or data transformation programs. Familiarity with healthcare, insurance, or benefits administration data environments. Experience applying data governance, privacy, and security best practices in AI/ML solutions. Education: Bachelor's degree in Computer Science, Data Science, Engineering, or a related discipline. Master's degree preferred. Equivalent professional experience will be considered in lieu of a degree. Clearance: Must be a U.S. citizen and be able to obtain an OPM Public Trust clearance. If you are looking for a fun and challenging environment with talented, motivated people to work with, CTEC is the right place for you. In addition to employee salary, we offer an array of employee benefits including: Paid vacation & Sick leave Health insurance coverage Career training Performance bonus programs 401K contribution & Employer Match 11 Federal Holidays
