Institute of Foundation Models
Sunnyvale, California
Job Description Job Description About the Institute of Foundation Models The Institute of Foundation Models is a dedicated research lab focused on building, understanding, using, and risk-managing foundation models. Our mission is to advance AI research, support the next generation of AI builders, and develop impactful systems that improve how frontier models are trained, evaluated, deployed, and governed. As part of our team, you will work closely with researchers, machine learning engineers, data scientists, software engineers, and product teams on some of the most important challenges in AI development. You will contribute to systems that help measure model quality, identify failure modes, and improve the reliability, safety, and readiness of model releases. The Role We are looking for an Eval360 - Error Analysis Engineer to help build, improve, and operate Eval360, an evaluation service that serves as a quality gate for AI models. This person will focus specifically on error analysis : understanding where models fail, why they fail, how those failures should be categorized, and how evaluation systems can better detect, measure, and prevent these issues before models are released. You will collaborate with researchers, machine learning engineers, product managers, data scientists, and platform teams to develop AI evaluation applications and internal tools based on next-generation AI research. You will be part of a cross-functional team responsible for the full software development lifecycle, from requirements gathering and system design to implementation, deployment, monitoring, debugging, documentation, and continuous improvement. The ideal candidate is comfortable working across the stack, including front-end interfaces for reviewing errors, back-end evaluation pipelines, data analysis workflows, model evaluation infrastructure, databases, dashboards, and APIs. This person should have strong software engineering skills, excellent analytical judgment, and the ability to turn ambiguous model failures into structured insights that improve evaluation quality. Key Responsibilities • Collaborate with researchers, machine learning engineers, data scientists, product managers, and internal stakeholders to implement innovative software solutions for Eval360 and related model evaluation workflows. • Build and improve Eval360 as an evaluation service that acts as a quality gate for model development, model comparison, and model release decisions. • Perform deep error analysis on model outputs, including identifying failure patterns, categorizing issues, tracing root causes, and proposing improvements to evaluation methodology. • Develop tools, workflows, and dashboards that make it easier for researchers and engineers to inspect model failures, compare model behavior, and understand quality regressions. • Design and implement client-side and server-side architecture for evaluation review systems, error analysis interfaces, reporting tools, and internal evaluation applications. • Develop responsive, usable interfaces that support error triage, annotation review, evaluation debugging, and model quality investigation. • Build and maintain back-end services, APIs, data pipelines, and integrations that support evaluation execution, results storage, analysis, and reporting. • Test software to ensure responsiveness, correctness, reliability, and efficiency across evaluation workflows. • Troubleshoot, debug, and upgrade evaluation systems, including identifying issues in data processing, evaluation metrics, model output handling, job orchestration, and user-facing analysis tools. • Create and maintain security, access control, and data protection settings for evaluation data, model outputs, annotations, and internal tooling. • Write clear technical documentation for Eval360 systems, error taxonomies, evaluation workflows, debugging procedures, and user-facing tools. • Work with researchers, data scientists, analysts, and machine learning engineers to improve evaluation quality, model diagnostics, and failure-mode visibility. • Keep track of new development tools, evaluation frameworks, model analysis methods, data quality techniques, and architectures relevant to AI evaluation systems. • Contribute to the design of error taxonomies, evaluation rubrics, quality thresholds, regression detection methods, and model readiness criteria. • Help ensure Eval360 produces reliable, interpretable, and actionable signals for model quality gates. • Contribute to research publications, technical reports, internal knowledge sharing, and external presentations where appropriate. • Contribute to intellectual property and thought leadership in AI evaluation, error analysis, model quality measurement, and evaluation infrastructure. • Perform all other duties as reasonably directed by the line manager that are aligned with these functional objectives. Academic Qualifications • Bachelor's degree in Computer Science, Machine Learning, Data Science, Software Engineering, Statistics, or a related technical field required. • Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related field preferred. Professional Experience • Proven experience as a Software Engineer, Full Stack Developer, Machine Learning Evaluation Engineer, Data Scientist, AI Engineer, or similar role. • Experience building software systems for AI, machine learning, data analysis, evaluation, annotation, experimentation, or model monitoring. • Experience working with AI algorithms and the ability to develop systems that accommodate AI-related requirements. • Experience performing error analysis, model evaluation, data quality analysis, or failure-mode investigation for machine learning or language model systems. • Experience developing internal applications, dashboards, review tools, or web-based workflows for technical users. • Familiarity with common software stacks, including front-end frameworks, back-end services, databases, APIs, and cloud or internal infrastructure. • Familiarity with GitHub, Git, CI/CD workflows, and collaborative software development practices. • Knowledge of front-end languages and libraries such as HTML, CSS, JavaScript, TypeScript, React, Angular, or similar technologies. • Knowledge of back-end languages and frameworks such as Python, Java, C#, Node.js, FastAPI, Flask, Django, or similar technologies. • Familiarity with databases such as MySQL, PostgreSQL, MongoDB, or other structured and unstructured data stores. • Familiarity with evaluation frameworks, experiment tracking systems, data pipelines, or machine learning infrastructure is strongly preferred. • Ability to analyze complex model outputs and translate qualitative failures into structured, measurable categories. • Strong problem-solving and troubleshooting skills, especially for ambiguous technical issues involving models, data, metrics, and software systems. • Effective communication and collaboration skills, with the ability to work across research, engineering, data, and product teams. • Strong attention to detail and a high bar for evaluation quality, reliability, and interpretability. Preferred Qualifications • Experience with large language models, foundation models, multimodal models, or model evaluation systems. • Experience designing or using error taxonomies, evaluation rubrics, benchmark datasets, human evaluation workflows, or automated grading systems. • Experience with Python-based data analysis tools such as pandas, NumPy, Jupyter, or similar. • Experience with visualization or dashboarding tools for model quality analysis. • Experience with distributed systems, job queues, workflow orchestration, or large-scale data processing. • Experience working in a research environment or with fast-moving AI product and model teams. Salary Range The posted salary range represents the company's good faith estimate of the compensation for this position upon hire. The actual compensation offered may vary within this range depending on individual qualifications, including but not limited to relevant skills, experience, education, certifications, geographic location, and specific business needs. Visa Sponsorship This position is eligible for visa sponsorship. Benefits Include • Comprehensive medical, dental, and vision benefits • Bonus • 401K plan • Generous paid time off, sick leave, and holidays • Paid parental leave • Employee assistance program • Life insurance and disability insurance
09/18/2026
Full time
Job Description Job Description About the Institute of Foundation Models The Institute of Foundation Models is a dedicated research lab focused on building, understanding, using, and risk-managing foundation models. Our mission is to advance AI research, support the next generation of AI builders, and develop impactful systems that improve how frontier models are trained, evaluated, deployed, and governed. As part of our team, you will work closely with researchers, machine learning engineers, data scientists, software engineers, and product teams on some of the most important challenges in AI development. You will contribute to systems that help measure model quality, identify failure modes, and improve the reliability, safety, and readiness of model releases. The Role We are looking for an Eval360 - Error Analysis Engineer to help build, improve, and operate Eval360, an evaluation service that serves as a quality gate for AI models. This person will focus specifically on error analysis : understanding where models fail, why they fail, how those failures should be categorized, and how evaluation systems can better detect, measure, and prevent these issues before models are released. You will collaborate with researchers, machine learning engineers, product managers, data scientists, and platform teams to develop AI evaluation applications and internal tools based on next-generation AI research. You will be part of a cross-functional team responsible for the full software development lifecycle, from requirements gathering and system design to implementation, deployment, monitoring, debugging, documentation, and continuous improvement. The ideal candidate is comfortable working across the stack, including front-end interfaces for reviewing errors, back-end evaluation pipelines, data analysis workflows, model evaluation infrastructure, databases, dashboards, and APIs. This person should have strong software engineering skills, excellent analytical judgment, and the ability to turn ambiguous model failures into structured insights that improve evaluation quality. Key Responsibilities • Collaborate with researchers, machine learning engineers, data scientists, product managers, and internal stakeholders to implement innovative software solutions for Eval360 and related model evaluation workflows. • Build and improve Eval360 as an evaluation service that acts as a quality gate for model development, model comparison, and model release decisions. • Perform deep error analysis on model outputs, including identifying failure patterns, categorizing issues, tracing root causes, and proposing improvements to evaluation methodology. • Develop tools, workflows, and dashboards that make it easier for researchers and engineers to inspect model failures, compare model behavior, and understand quality regressions. • Design and implement client-side and server-side architecture for evaluation review systems, error analysis interfaces, reporting tools, and internal evaluation applications. • Develop responsive, usable interfaces that support error triage, annotation review, evaluation debugging, and model quality investigation. • Build and maintain back-end services, APIs, data pipelines, and integrations that support evaluation execution, results storage, analysis, and reporting. • Test software to ensure responsiveness, correctness, reliability, and efficiency across evaluation workflows. • Troubleshoot, debug, and upgrade evaluation systems, including identifying issues in data processing, evaluation metrics, model output handling, job orchestration, and user-facing analysis tools. • Create and maintain security, access control, and data protection settings for evaluation data, model outputs, annotations, and internal tooling. • Write clear technical documentation for Eval360 systems, error taxonomies, evaluation workflows, debugging procedures, and user-facing tools. • Work with researchers, data scientists, analysts, and machine learning engineers to improve evaluation quality, model diagnostics, and failure-mode visibility. • Keep track of new development tools, evaluation frameworks, model analysis methods, data quality techniques, and architectures relevant to AI evaluation systems. • Contribute to the design of error taxonomies, evaluation rubrics, quality thresholds, regression detection methods, and model readiness criteria. • Help ensure Eval360 produces reliable, interpretable, and actionable signals for model quality gates. • Contribute to research publications, technical reports, internal knowledge sharing, and external presentations where appropriate. • Contribute to intellectual property and thought leadership in AI evaluation, error analysis, model quality measurement, and evaluation infrastructure. • Perform all other duties as reasonably directed by the line manager that are aligned with these functional objectives. Academic Qualifications • Bachelor's degree in Computer Science, Machine Learning, Data Science, Software Engineering, Statistics, or a related technical field required. • Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related field preferred. Professional Experience • Proven experience as a Software Engineer, Full Stack Developer, Machine Learning Evaluation Engineer, Data Scientist, AI Engineer, or similar role. • Experience building software systems for AI, machine learning, data analysis, evaluation, annotation, experimentation, or model monitoring. • Experience working with AI algorithms and the ability to develop systems that accommodate AI-related requirements. • Experience performing error analysis, model evaluation, data quality analysis, or failure-mode investigation for machine learning or language model systems. • Experience developing internal applications, dashboards, review tools, or web-based workflows for technical users. • Familiarity with common software stacks, including front-end frameworks, back-end services, databases, APIs, and cloud or internal infrastructure. • Familiarity with GitHub, Git, CI/CD workflows, and collaborative software development practices. • Knowledge of front-end languages and libraries such as HTML, CSS, JavaScript, TypeScript, React, Angular, or similar technologies. • Knowledge of back-end languages and frameworks such as Python, Java, C#, Node.js, FastAPI, Flask, Django, or similar technologies. • Familiarity with databases such as MySQL, PostgreSQL, MongoDB, or other structured and unstructured data stores. • Familiarity with evaluation frameworks, experiment tracking systems, data pipelines, or machine learning infrastructure is strongly preferred. • Ability to analyze complex model outputs and translate qualitative failures into structured, measurable categories. • Strong problem-solving and troubleshooting skills, especially for ambiguous technical issues involving models, data, metrics, and software systems. • Effective communication and collaboration skills, with the ability to work across research, engineering, data, and product teams. • Strong attention to detail and a high bar for evaluation quality, reliability, and interpretability. Preferred Qualifications • Experience with large language models, foundation models, multimodal models, or model evaluation systems. • Experience designing or using error taxonomies, evaluation rubrics, benchmark datasets, human evaluation workflows, or automated grading systems. • Experience with Python-based data analysis tools such as pandas, NumPy, Jupyter, or similar. • Experience with visualization or dashboarding tools for model quality analysis. • Experience with distributed systems, job queues, workflow orchestration, or large-scale data processing. • Experience working in a research environment or with fast-moving AI product and model teams. Salary Range The posted salary range represents the company's good faith estimate of the compensation for this position upon hire. The actual compensation offered may vary within this range depending on individual qualifications, including but not limited to relevant skills, experience, education, certifications, geographic location, and specific business needs. Visa Sponsorship This position is eligible for visa sponsorship. Benefits Include • Comprehensive medical, dental, and vision benefits • Bonus • 401K plan • Generous paid time off, sick leave, and holidays • Paid parental leave • Employee assistance program • Life insurance and disability insurance
Job Description Job Description Our mission is to create the Experience of a Lifetime for our employees, so they can, in turn, create the Experience of a Lifetime for our guests. We own and operate the most renowned destination resorts in the world as well as regional and local ski areas outside major cities, and connect them all through one unrivaled network. We are looking for ambitious leaders, innovators and creators to join our talented team. If you're ready to pursue your fullest potential, we want to get to know you! Candidates for year-round positions are reviewed on a rolling basis. Applications will be accepted up to 90 days after the posting date, or until the position is filled (whichever is first). Job Summary: We are looking for a curious, driven, innovative machine learning engineer who takes initiative to solve problems and create environments that accelerate the development, deployment, and usage of data science models and AI to drive greater organizational impact. The Data Science & Data Engineering team within the Enterprise Analytics organization builds data assets, predictive models, analytical applications, and platforms across the organization. Our team collaborates with business stakeholders, analysts, and technology teams to tackle high-impact use cases with state-of-the-art models and tools to grow the business, streamline costs, and improve guest experiences. Job Specifications: Starting Wage: $140,000 - $185,000 + Annual Bonus Employment Type: Year Round Shift Type: Full Time hours Minimum Age: At least 18 years of age Housing Availability: No Job Responsibilities: Productionize ML models developed by data science into reliable, monitored, maintainable systems. Build model data foundations that ensure training, inference, monitoring, and analytics data are trustworthy and scalable. Architect ML platform patterns in Databricks that bring reliability, consistency, governance, performance, and cost discipline to ML and data workflows. Identify and scope opportunities for ML engineering across the business for high-impact. Develop reusable tools , libraries, standards, documentation, and production-readiness practices to enable data science and data engineering teams. Develop analytical and model-powered applications that turn data and ML outputs into usable business workflows for end users. Prepare the platform for future AI engineering , including LLM and agent-based systems, as the organization matures. Provide technical leadership and mentoring across engineering, architecture, and development including design and code reviews. Job Requirements: Technical Skills: Quantitative Foundation : B.S. degree in a quantitative field (e.g., Computer Science, Mathematics, Statistics, Economics, Operations Research, Engineering). Software Engineering Fundamentals: write clean, modular, testable, maintainable code and understand how to structure production-grade systems rather than one-off notebooks or scripts. Python and SQL Proficiency: strong in Python and SQL for building data pipelines, automation, model integrations, analytical workflows, and production services. Data Modeling and Pipeline Design: understand how to design reliable, well-structured data assets, including curated tables, feature datasets, batch pipelines, orchestration, data quality checks, and lineage. ML Lifecycle Fluency: understand the full model lifecycle: data collection, exploration, model development, validation, deployment, monitoring, retraining, and retirement. Production ML Patterns: understand core MLOps patterns such as model registries, feature/data versioning, reproducible environments, testing/validation, monitoring, and rollback. Cloud and Platform Engineering: You are comfortable working in cloud-based data and ML environments and understand the foundations of permissions, environments, jobs, services, storage, networking, and cost-aware architecture. Databricks Expertise : You're familiar and experienced with the core parts of Spark, Unity Catalog, Delta Lake, Databricks Workflows, MLflow, model registry patterns, job/cluster optimization, and governance. DevOps Practices: You use modern engineering practices such as Git, CI/CD, automated testing, code review, dependency management, environment management, and observability. Application Development : You can build applications, APIs, dashboards, or workflow tools that sit on top of data and model outputs. System Design: You can reason through tradeoffs across reliability, latency, scale, cost, governance, maintainability, and ease of use. Soft Skills: Curious : bring intellectual curiosity, an inquisitive nature, and a desire to deepen your knowledge and continue learning. Ownership : take responsibility to proactively advance projects, contribute to the organization, and develop the best solutions. Communication: explain technical concepts, risks, tradeoffs, and recommendations clearly to technical and non-technical audiences. Collaboration: work effectively cross-functionally with data scientists, data engineers, analysts, application engineers, product partners, and business stakeholders. Pragmatism : You know how to balance ideal architecture with business urgency, team maturity, operational constraints, and the need to ship. Preferred qualifications: A graduate degree (Masters or PhD) in a quantitative field Experience with dbt (Core) for modular data modeling, including testing, documentation, and dependency management Experience with AI engineer to use, build, and monitor agentic solutions The expected Total Compensation for this role is $140,000 - $185,000 + Annual Bonus. Individual compensation decisions are based on a variety of factors. Job Benefits Ski/Mountain Perks! Free passes for employees, employee discounted lift tickets for friends and family AND free ski lessons MORE employee discounts on lodging, food, gear, and mountain shuttles 401(k) Retirement Plan Employee Assistance Program Excellent training and professional development Full Time roles are eligible for the above, plus: Health Insurance; Medical Insurance, Dental Insurance, and Vision Insurance plans (for eligible seasonal employees after working 500 hours) Free ski passes for dependents Critical Illness and Accident plans Employees can work remotely from British Columbia, Washington D.C., and the 16 U.S. states in which we currently operate. This includes: California, Colorado, Indiana, Michigan, Minnesota, Missouri, New Hampshire, New York, Nevada, Ohio, Pennsylvania, Utah, Vermont, Washington State, Wisconsin, and Wyoming. Please note that the ability to work in person or off-site, and the particulars related to such work, are subject to change at any time; and, accordingly, the Company reserves the right to change its policies and/or require in-person/in-office work or off-site work at any time in its sole discretion. In completing this application, and when submitting related documentation, applicants may redact information that identifies their age, date of birth, and/or dates of attendance at or graduation from an educational institution. We follow all federal, state, and local laws including restrictions on child/minor labor. Minors hired into this position will not be asked or permitted to engage in any activities restricted to adult workers. Vail Resorts is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, protected veteran status or any other status protected by applicable law. Requisition ID 517322 Reference Date: 09/05/2026 Job Code Function: Data Science
09/17/2026
Full time
Job Description Job Description Our mission is to create the Experience of a Lifetime for our employees, so they can, in turn, create the Experience of a Lifetime for our guests. We own and operate the most renowned destination resorts in the world as well as regional and local ski areas outside major cities, and connect them all through one unrivaled network. We are looking for ambitious leaders, innovators and creators to join our talented team. If you're ready to pursue your fullest potential, we want to get to know you! Candidates for year-round positions are reviewed on a rolling basis. Applications will be accepted up to 90 days after the posting date, or until the position is filled (whichever is first). Job Summary: We are looking for a curious, driven, innovative machine learning engineer who takes initiative to solve problems and create environments that accelerate the development, deployment, and usage of data science models and AI to drive greater organizational impact. The Data Science & Data Engineering team within the Enterprise Analytics organization builds data assets, predictive models, analytical applications, and platforms across the organization. Our team collaborates with business stakeholders, analysts, and technology teams to tackle high-impact use cases with state-of-the-art models and tools to grow the business, streamline costs, and improve guest experiences. Job Specifications: Starting Wage: $140,000 - $185,000 + Annual Bonus Employment Type: Year Round Shift Type: Full Time hours Minimum Age: At least 18 years of age Housing Availability: No Job Responsibilities: Productionize ML models developed by data science into reliable, monitored, maintainable systems. Build model data foundations that ensure training, inference, monitoring, and analytics data are trustworthy and scalable. Architect ML platform patterns in Databricks that bring reliability, consistency, governance, performance, and cost discipline to ML and data workflows. Identify and scope opportunities for ML engineering across the business for high-impact. Develop reusable tools , libraries, standards, documentation, and production-readiness practices to enable data science and data engineering teams. Develop analytical and model-powered applications that turn data and ML outputs into usable business workflows for end users. Prepare the platform for future AI engineering , including LLM and agent-based systems, as the organization matures. Provide technical leadership and mentoring across engineering, architecture, and development including design and code reviews. Job Requirements: Technical Skills: Quantitative Foundation : B.S. degree in a quantitative field (e.g., Computer Science, Mathematics, Statistics, Economics, Operations Research, Engineering). Software Engineering Fundamentals: write clean, modular, testable, maintainable code and understand how to structure production-grade systems rather than one-off notebooks or scripts. Python and SQL Proficiency: strong in Python and SQL for building data pipelines, automation, model integrations, analytical workflows, and production services. Data Modeling and Pipeline Design: understand how to design reliable, well-structured data assets, including curated tables, feature datasets, batch pipelines, orchestration, data quality checks, and lineage. ML Lifecycle Fluency: understand the full model lifecycle: data collection, exploration, model development, validation, deployment, monitoring, retraining, and retirement. Production ML Patterns: understand core MLOps patterns such as model registries, feature/data versioning, reproducible environments, testing/validation, monitoring, and rollback. Cloud and Platform Engineering: You are comfortable working in cloud-based data and ML environments and understand the foundations of permissions, environments, jobs, services, storage, networking, and cost-aware architecture. Databricks Expertise : You're familiar and experienced with the core parts of Spark, Unity Catalog, Delta Lake, Databricks Workflows, MLflow, model registry patterns, job/cluster optimization, and governance. DevOps Practices: You use modern engineering practices such as Git, CI/CD, automated testing, code review, dependency management, environment management, and observability. Application Development : You can build applications, APIs, dashboards, or workflow tools that sit on top of data and model outputs. System Design: You can reason through tradeoffs across reliability, latency, scale, cost, governance, maintainability, and ease of use. Soft Skills: Curious : bring intellectual curiosity, an inquisitive nature, and a desire to deepen your knowledge and continue learning. Ownership : take responsibility to proactively advance projects, contribute to the organization, and develop the best solutions. Communication: explain technical concepts, risks, tradeoffs, and recommendations clearly to technical and non-technical audiences. Collaboration: work effectively cross-functionally with data scientists, data engineers, analysts, application engineers, product partners, and business stakeholders. Pragmatism : You know how to balance ideal architecture with business urgency, team maturity, operational constraints, and the need to ship. Preferred qualifications: A graduate degree (Masters or PhD) in a quantitative field Experience with dbt (Core) for modular data modeling, including testing, documentation, and dependency management Experience with AI engineer to use, build, and monitor agentic solutions The expected Total Compensation for this role is $140,000 - $185,000 + Annual Bonus. Individual compensation decisions are based on a variety of factors. Job Benefits Ski/Mountain Perks! Free passes for employees, employee discounted lift tickets for friends and family AND free ski lessons MORE employee discounts on lodging, food, gear, and mountain shuttles 401(k) Retirement Plan Employee Assistance Program Excellent training and professional development Full Time roles are eligible for the above, plus: Health Insurance; Medical Insurance, Dental Insurance, and Vision Insurance plans (for eligible seasonal employees after working 500 hours) Free ski passes for dependents Critical Illness and Accident plans Employees can work remotely from British Columbia, Washington D.C., and the 16 U.S. states in which we currently operate. This includes: California, Colorado, Indiana, Michigan, Minnesota, Missouri, New Hampshire, New York, Nevada, Ohio, Pennsylvania, Utah, Vermont, Washington State, Wisconsin, and Wyoming. Please note that the ability to work in person or off-site, and the particulars related to such work, are subject to change at any time; and, accordingly, the Company reserves the right to change its policies and/or require in-person/in-office work or off-site work at any time in its sole discretion. In completing this application, and when submitting related documentation, applicants may redact information that identifies their age, date of birth, and/or dates of attendance at or graduation from an educational institution. We follow all federal, state, and local laws including restrictions on child/minor labor. Minors hired into this position will not be asked or permitted to engage in any activities restricted to adult workers. Vail Resorts is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, protected veteran status or any other status protected by applicable law. Requisition ID 517322 Reference Date: 09/05/2026 Job Code Function: Data Science
Job Description Job Description Staff / Principal Platform Engineer Location: New York City Hybrid Department: AI Platform & Infrastructure Team Reports to: Vangie Shue - Principal Engineering Manager About AppGate AppGate secures and protects an organization's most valuable assets with its high performance Zero Trust Network Access (ZTNA) solution and Cyber Advisory Services. AppGate ZTNA is the only direct-routed Zero Trust solution built for peak performance, superior protection and seamless interoperability. AppGate Cyber Advisory Services harden your security posture and ensure business continuity. AppGate safeguards Fortune 500 enterprises and government agencies worldwide. Learn more at About the Role As we expand our platform, we are standing up a new AI Platform & Infrastructure team: the engine room of AppGate's AI strategy. This team owns the infrastructure layer that every next-generation security capability is built on, from network observability to AI-driven threat detection and the secure operation of emerging Agentic AI systems. We're looking for a Staff or Principal Platform Engineer to build and operate the foundational platform behind AppGate's AI products. You combine deep DevOps and cloud infrastructure expertise with hands-on experience operationalizing AI/ML systems, and you treat observability as a first-class engineering discipline. This is a rare opportunity to join a small, private, high-impact company where your work directly shapes the architecture, reliability and core platform that defines the future of security. You'll own the platform spanning APIs, cloud and self-managed solutions and AI/ML infrastructure, and you'll make it fast, reliable and observable at scale. This is a high-leverage, hands-on role for a senior engineer who sets technical direction and still ships. Key Responsibilities Build the Platform: design, build and operate the cloud infrastructure, services and pipelines that AppGate's AI and cloud products run on. Strong experience with self-managed technologies (kafka, elasticsearch) and Kubernetes are a must. Infrastructure as Code & Deployment Orchestration: Terraform and Helm for cloud provisioning, service deployment and configuration management. Implement Observability: instrument APIs, cloud services and AI/ML infrastructure with metrics, logging, tracing and alerting, and define SLOs and operational health metrics that teams trust. Data Platform: real-time and batch data ingestion pipelines, feature stores and data quality. Integrations: third-party connectors, APIs and platform integrations. Operationalize AI/ML: build model serving and inference pipelines, experiment tracking and the MLOps tooling for deployment, versioning, drift monitoring and lifecycle management. Engineer for reliability & automation: apply SRE practices to reduce toil, improve resilience and keep latency and uptime within target across the platform. Automate everything - deliver infrastructure-as-code, CI/CD and self-service tooling so product teams ship safely and quickly. Set technical direction: define platform standards, architecture and best practices, and raise the engineering bar through design reviews and mentorship. Collaborate cross-functionally: partner with data scientists, product teams and leadership to align platform investment with AppGate's strategic vision. Required Qualifications Experience: extensive platform, infrastructure or SRE engineering experience, with a track record of operating production systems at scale. Staff-level candidates typically bring 8+ years and Principal-level candidates 12+ years, though we hire on demonstrated impact. DevOps depth: strong command of infrastructure-as-code (Terraform or equivalent), CI/CD, containers and orchestration (Docker, Kubernetes), and cloud platforms (AWS). Observability expertise: hands-on experience implementing observability across APIs, cloud services and distributed systems using tools such as Prometheus, Grafana, OpenTelemetry, the ELK stack or comparable, including SLO and error-budget practice. Data platform skills: familiarity with real-time and batch ingestion pipelines, feature stores and data quality at production scale. Engineering craft: fluency in a primary backend language (Python, Go or similar) and a strong bias toward automation, testing and reliable, maintainable systems. Leadership: a record of setting technical direction, leading complex initiatives across teams, mentoring senior engineers, while still being very hands-on. Mindset: pragmatic, rigorous and ownership-driven. You thrive in a small, fast-moving environment and enjoy building foundations others depend on. Preferred Qualifications AI/ML infrastructure: experience building or operating model serving, inference pipelines and MLOps tooling such as MLflow, Kubeflow, SageMaker or equivalent, including model deployment, versioning and drift monitoring. Networking & Zero Trust fundamentals: working knowledge of the network and routing layer beneath modern access solutions - TCP/IP, TLS, tunneling/overlay networks, packet routing and filtering, DNS and firewalling - and familiarity with Zero Trust Network Access (ZTNA) or adjacent domains (VPN, SDP, SASE, software-defined networking). You can reason about traffic paths, latency and throughput end-to-end, and instrument the network as a first-class observability signal. Compensation Staff: 185k-225k base Principal: 215k-270k base We offer performance bonuses and considerable equity. AppGate is An Equal Opportunity/Affirmative Action Employer and a federal contractor subject to the Rehabilitation Act of 1973 and the Vietnam Era Veterans Readjustment Assistance Act of 1974 as amended, and their corresponding regulations. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class. Further, AppGate is an affirmative action employer committed to taking positive steps to employ, advance in employment and otherwise afford equal employment opportunity to protected veterans and individuals with disabilities. In furtherance of AppGate's policy regarding affirmative action and equal employment opportunity, AppGate has developed a written affirmative action program. This program is available for review upon request by any applicant or employee during normal business hours by contacting the company's EEO Coordinator.
09/15/2026
Full time
Job Description Job Description Staff / Principal Platform Engineer Location: New York City Hybrid Department: AI Platform & Infrastructure Team Reports to: Vangie Shue - Principal Engineering Manager About AppGate AppGate secures and protects an organization's most valuable assets with its high performance Zero Trust Network Access (ZTNA) solution and Cyber Advisory Services. AppGate ZTNA is the only direct-routed Zero Trust solution built for peak performance, superior protection and seamless interoperability. AppGate Cyber Advisory Services harden your security posture and ensure business continuity. AppGate safeguards Fortune 500 enterprises and government agencies worldwide. Learn more at About the Role As we expand our platform, we are standing up a new AI Platform & Infrastructure team: the engine room of AppGate's AI strategy. This team owns the infrastructure layer that every next-generation security capability is built on, from network observability to AI-driven threat detection and the secure operation of emerging Agentic AI systems. We're looking for a Staff or Principal Platform Engineer to build and operate the foundational platform behind AppGate's AI products. You combine deep DevOps and cloud infrastructure expertise with hands-on experience operationalizing AI/ML systems, and you treat observability as a first-class engineering discipline. This is a rare opportunity to join a small, private, high-impact company where your work directly shapes the architecture, reliability and core platform that defines the future of security. You'll own the platform spanning APIs, cloud and self-managed solutions and AI/ML infrastructure, and you'll make it fast, reliable and observable at scale. This is a high-leverage, hands-on role for a senior engineer who sets technical direction and still ships. Key Responsibilities Build the Platform: design, build and operate the cloud infrastructure, services and pipelines that AppGate's AI and cloud products run on. Strong experience with self-managed technologies (kafka, elasticsearch) and Kubernetes are a must. Infrastructure as Code & Deployment Orchestration: Terraform and Helm for cloud provisioning, service deployment and configuration management. Implement Observability: instrument APIs, cloud services and AI/ML infrastructure with metrics, logging, tracing and alerting, and define SLOs and operational health metrics that teams trust. Data Platform: real-time and batch data ingestion pipelines, feature stores and data quality. Integrations: third-party connectors, APIs and platform integrations. Operationalize AI/ML: build model serving and inference pipelines, experiment tracking and the MLOps tooling for deployment, versioning, drift monitoring and lifecycle management. Engineer for reliability & automation: apply SRE practices to reduce toil, improve resilience and keep latency and uptime within target across the platform. Automate everything - deliver infrastructure-as-code, CI/CD and self-service tooling so product teams ship safely and quickly. Set technical direction: define platform standards, architecture and best practices, and raise the engineering bar through design reviews and mentorship. Collaborate cross-functionally: partner with data scientists, product teams and leadership to align platform investment with AppGate's strategic vision. Required Qualifications Experience: extensive platform, infrastructure or SRE engineering experience, with a track record of operating production systems at scale. Staff-level candidates typically bring 8+ years and Principal-level candidates 12+ years, though we hire on demonstrated impact. DevOps depth: strong command of infrastructure-as-code (Terraform or equivalent), CI/CD, containers and orchestration (Docker, Kubernetes), and cloud platforms (AWS). Observability expertise: hands-on experience implementing observability across APIs, cloud services and distributed systems using tools such as Prometheus, Grafana, OpenTelemetry, the ELK stack or comparable, including SLO and error-budget practice. Data platform skills: familiarity with real-time and batch ingestion pipelines, feature stores and data quality at production scale. Engineering craft: fluency in a primary backend language (Python, Go or similar) and a strong bias toward automation, testing and reliable, maintainable systems. Leadership: a record of setting technical direction, leading complex initiatives across teams, mentoring senior engineers, while still being very hands-on. Mindset: pragmatic, rigorous and ownership-driven. You thrive in a small, fast-moving environment and enjoy building foundations others depend on. Preferred Qualifications AI/ML infrastructure: experience building or operating model serving, inference pipelines and MLOps tooling such as MLflow, Kubeflow, SageMaker or equivalent, including model deployment, versioning and drift monitoring. Networking & Zero Trust fundamentals: working knowledge of the network and routing layer beneath modern access solutions - TCP/IP, TLS, tunneling/overlay networks, packet routing and filtering, DNS and firewalling - and familiarity with Zero Trust Network Access (ZTNA) or adjacent domains (VPN, SDP, SASE, software-defined networking). You can reason about traffic paths, latency and throughput end-to-end, and instrument the network as a first-class observability signal. Compensation Staff: 185k-225k base Principal: 215k-270k base We offer performance bonuses and considerable equity. AppGate is An Equal Opportunity/Affirmative Action Employer and a federal contractor subject to the Rehabilitation Act of 1973 and the Vietnam Era Veterans Readjustment Assistance Act of 1974 as amended, and their corresponding regulations. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class. Further, AppGate is an affirmative action employer committed to taking positive steps to employ, advance in employment and otherwise afford equal employment opportunity to protected veterans and individuals with disabilities. In furtherance of AppGate's policy regarding affirmative action and equal employment opportunity, AppGate has developed a written affirmative action program. This program is available for review upon request by any applicant or employee during normal business hours by contacting the company's EEO Coordinator.
Design, build, and operate scalable and secure data platforms and data pipelines that support analytics, reporting, AI/ML, and self-service data across the firm. Duties include: 1. Develop and maintain reliable batch and real-time data pipelines and ETL/ELT workflows for ingesting, transforming, and delivering internal and external datasets to downstream users and systems; 2. Architect and implement end-to-end data acquisition and integrations for securities, market, and reference data from internal systems and external vendors (e.g., APIs, SFTP, data feeds, and cloud data marketplaces), including schema and change management; 3. Integrate internal and external financial datasets, and implement data quality and governance frameworks; 4. Deliver reliable, well-modeled data for decision making in partnership with engineering, data science, and business teams; 5. Implement and maintain data quality, metadata, data lineage, and role- or policy-based access control frameworks to ensure data integrity, consistency, and compliance with firm standards; 6. Design and deliver curated, well-modeled datasets and APIs in collaboration with software engineers, data scientists, and business stakeholders; 7. Provide production support, monitoring, performance optimization, and incident resolution for data platforms and pipelines. May telecommute part of the week from commuting distance to New York, NY in accordance with the companys flexible working policy. Position Requirements: A Bachelors degree or foreign equivalent in Computer Science, Computer Engineering, or a related field followed by 5 years of post-baccalaureate experience in a software engineering or data engineering-related occupation. Experience must include the following, which may have been gained concurrently: 1) 5 years of experience building and operating scalable data platforms and data pipelines for analytics and AI/ML workloads in a production environment; 2) 5 years of experience programming with Python, Scala, or Java; 3) 5 years of experience using SQL with relational databases, including MS SQL Server, PostgreSQL, MariaDB, or similar; 4) 4 years of experience designing and implementing ETL/ELT processes, including data modeling, schema management, partitioning, and query optimization, in cloud data warehouse or data lake/lakehouse environments; 5) 4 years of experience working with big-data or distributed compute frameworks, including Apache Spark, Hadoop, or Hive, to process large-scale datasets; 6) 3 years of experience integrating and monitoring financial market datasets, including market data, reference data, transactional data, and derived datasets (including curves and volatility surfaces); 7) 3 years of experience implementing data governance and data quality frameworks, including metadata management, data lineage, and role- or policy-based access controls; 8) 3 years of experience delivering reliable production data systems using CI/CD pipelines, automated testing, monitoring and alerting, and version control; 9) 3 years of experience providing production support for data platforms and pipelines. Job site: 280 Park Avenue, New York, NY 10017. Full-time. Salary: $175,000 to $225,000. JOB OPPORTUNITY QUALIFIES FOR EMPLOYEE INCENTIVE REFERRAL PROGRAM. To apply, email cover letter and resume, referencing Req. , to recruitment at elliottmgmt dot com.
09/15/2026
Design, build, and operate scalable and secure data platforms and data pipelines that support analytics, reporting, AI/ML, and self-service data across the firm. Duties include: 1. Develop and maintain reliable batch and real-time data pipelines and ETL/ELT workflows for ingesting, transforming, and delivering internal and external datasets to downstream users and systems; 2. Architect and implement end-to-end data acquisition and integrations for securities, market, and reference data from internal systems and external vendors (e.g., APIs, SFTP, data feeds, and cloud data marketplaces), including schema and change management; 3. Integrate internal and external financial datasets, and implement data quality and governance frameworks; 4. Deliver reliable, well-modeled data for decision making in partnership with engineering, data science, and business teams; 5. Implement and maintain data quality, metadata, data lineage, and role- or policy-based access control frameworks to ensure data integrity, consistency, and compliance with firm standards; 6. Design and deliver curated, well-modeled datasets and APIs in collaboration with software engineers, data scientists, and business stakeholders; 7. Provide production support, monitoring, performance optimization, and incident resolution for data platforms and pipelines. May telecommute part of the week from commuting distance to New York, NY in accordance with the companys flexible working policy. Position Requirements: A Bachelors degree or foreign equivalent in Computer Science, Computer Engineering, or a related field followed by 5 years of post-baccalaureate experience in a software engineering or data engineering-related occupation. Experience must include the following, which may have been gained concurrently: 1) 5 years of experience building and operating scalable data platforms and data pipelines for analytics and AI/ML workloads in a production environment; 2) 5 years of experience programming with Python, Scala, or Java; 3) 5 years of experience using SQL with relational databases, including MS SQL Server, PostgreSQL, MariaDB, or similar; 4) 4 years of experience designing and implementing ETL/ELT processes, including data modeling, schema management, partitioning, and query optimization, in cloud data warehouse or data lake/lakehouse environments; 5) 4 years of experience working with big-data or distributed compute frameworks, including Apache Spark, Hadoop, or Hive, to process large-scale datasets; 6) 3 years of experience integrating and monitoring financial market datasets, including market data, reference data, transactional data, and derived datasets (including curves and volatility surfaces); 7) 3 years of experience implementing data governance and data quality frameworks, including metadata management, data lineage, and role- or policy-based access controls; 8) 3 years of experience delivering reliable production data systems using CI/CD pipelines, automated testing, monitoring and alerting, and version control; 9) 3 years of experience providing production support for data platforms and pipelines. Job site: 280 Park Avenue, New York, NY 10017. Full-time. Salary: $175,000 to $225,000. JOB OPPORTUNITY QUALIFIES FOR EMPLOYEE INCENTIVE REFERRAL PROGRAM. To apply, email cover letter and resume, referencing Req. , to recruitment at elliottmgmt dot com.
Job Description Job Description Work Arrangement: Dallas-based / Hybrid Visa Sponsorship: Not available. Candidates must already be authorized to work in the United States without current or future employer sponsorship. Job Summary We are seeking a highly experienced Senior MLOps Engineer with strong hands-on Snowflake experience to support enterprise machine learning platforms and production ML workloads. The ideal candidate has hands-on experience taking machine learning models from experimentation through production and building the deployment pipelines, monitoring, automation, infrastructure, and governance capabilities required to operate ML solutions reliably at enterprise scale. This role will work closely with Data Scientists, ML Engineers, Data Engineers, Cloud Engineers, and enterprise platform teams. Key Responsibilities Design, build, and maintain enterprise-grade MLOps platforms and pipelines. Operationalize machine learning models developed by Data Science teams. Build automated ML workflows covering training, validation, deployment, monitoring, retraining, and retirement. Implement CI/CD pipelines specifically for machine learning workloads. Establish model registry, versioning, lineage, artifact management, and reproducibility. Implement model monitoring, data drift detection, model drift detection, prediction-quality monitoring, and alerting. Integrate ML workloads with Snowflake-based enterprise data environments . Build and optimize Python- and SQL-based data and ML pipelines. Support Snowflake data ingestion, transformation, compute, security, and ML integrations. Containerize ML workloads using Docker and deploy workloads through Kubernetes or comparable orchestration platforms. Implement logging, observability, alerting, and production support processes. Automate deployment and infrastructure provisioning using modern DevOps and Infrastructure-as-Code practices. Support model governance, approval workflows, lineage, auditability, and access controls. Troubleshoot production ML pipelines, model-serving infrastructure, Snowflake integrations, and performance issues. Develop reusable MLOps frameworks, standards, templates, and best practices. Mandatory Qualifications Candidates must have hands-on production experience in both MLOps and Snowflake . MLOps - Required Strong production experience with: ML model deployment and operationalization Model lifecycle management ML CI/CD Experiment tracking Model registry and versioning Automated model validation Model monitoring Data and model drift detection Retraining pipelines Pipeline orchestration Production troubleshooting Experience with one or more of the following: ML flow Kubeflow AWS SageMaker Azure Machine Learning Airflow Argo Workflows Prefect Dagster Equivalent enterprise MLOps platforms Snowflake - Required Strong hands-on Snowflake experience including: Snowflake architecture Databases, schemas, tables, and views Virtual warehouses Compute management Snowflake security and RBAC Data ingestion and transformation Performance optimization Python integration Snowflake integration with ML pipelines Experience with the following is strongly preferred: Snowpark Snowpark Python Snowflake ML Snowflake Model Registry Snowflake Feature Store Snowflake Tasks and Streams Dynamic Tables Snowpipe Cortex / Snowflake AI capabilities Additional Required Technical Skills Strong Python Strong SQL Git REST APIs Linux Shell scripting Docker CI/CD Cloud platforms such as AWS, Azure, or GCP Preferred Skills Experience with: Kubernetes Terraform GitHub Actions Jenkins GitLab CI/CD Azure DevOps dbt Spark Kafka Grafana CloudWatch Evidently Education and Experience Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Machine Learning, or related field. 6+ years of software, cloud, data, or ML engineering experience. 3+ years of hands-on production MLOps experience. Strong hands-on Snowflake experience. Experience deploying ML models into production. Experience implementing ML CI/CD pipelines. Strong Python and SQL skills. Experience with Docker and cloud infrastructure. Work Authorization This position does not provide visa sponsorship. Candidates must be currently authorized to work in the United States without employer sponsorship and must not require sponsorship now or in the future. Company Description About KAPI Advisors LLC KAPI Advisors LLC is a forward-thinking boutique firm at the intersection of AI, Machine Learning, Data Analytics, Generative AI, Mathematical Optimization, and Cloud Platform Engineering. We build highly personalized, cutting-edge solutions tailored to the specific needs of each client - empowering organizations with powerful tools to unlock new business opportunities, operational efficiencies, and platform reliability at scale. At KAPI Advisors, we are passionate about solving complex, real-world challenges through technology. Our capabilities span intelligent agent-based systems, advanced data analytics, optimization algorithms, and robust cloud infrastructure - all designed to work together seamlessly. Our offerings include Generative AI systems that enable automation and intelligent decision-making, ML models that surface actionable insights, Mathematical Optimization techniques for supply chain management, resource allocation, and logistics, and Site Reliability Engineering practices that ensure the platforms powering these solutions remain performant, resilient, and production-ready. We believe that great AI and data products are only as strong as the infrastructure beneath them. That's why our SRE and DevOps practice is central to everything we build - from designing observability frameworks and incident response playbooks, to implementing chaos engineering, disaster recovery, and developer productivity tooling that reduces toil and accelerates delivery. As a boutique firm, we offer the agility and depth that larger organizations simply cannot match. Our team works directly with clients to understand their unique challenges and craft tailored strategies that deliver both immediate impact and long-term resilience. Whether you're looking to scale an AI platform, modernize your cloud infrastructure, or build the reliability engineering culture your engineering team deserves - KAPI Advisors is the partner built for it. Company Description About KAPI Advisors LLC KAPI Advisors LLC is a forward-thinking boutique firm at the intersection of AI, Machine Learning, Data Analytics, Generative AI, Mathematical Optimization, and Cloud Platform Engineering. We build highly personalized, cutting-edge solutions tailored to the specific needs of each client - empowering organizations with powerful tools to unlock new business opportunities, operational efficiencies, and platform reliability at scale. At KAPI Advisors, we are passionate about solving complex, real-world challenges through technology. Our capabilities span intelligent agent-based systems, advanced data analytics, optimization algorithms, and robust cloud infrastructure - all designed to work together seamlessly. Our offerings include Generative AI systems that enable automation and intelligent decision-making, ML models that surface actionable insights, Mathematical Optimization techniques for supply chain management, resource allocation, and logistics, and Site Reliability Engineering practices that ensure the platforms powering these solutions remain performant, resilient, and production-ready. We believe that great AI and data products are only as strong as the infrastructure beneath them. That's why our SRE and DevOps practice is central to everything we build - from designing observability frameworks and incident response playbooks, to implementing chaos engineering, disaster recovery, and developer productivity tooling that reduces toil and accelerates delivery. As a boutique firm, we offer the agility and depth that larger organizations simply cannot match. Our team works directly with clients to understand their unique challenges and craft tailored strategies that deliver both immediate impact and long-term resilience. Whether you're looking to scale an AI platform, modernize your cloud infrastructure, or build the reliability engineering culture your engineering team deserves - KAPI Advisors is the partner built for it.
09/15/2026
Full time
Job Description Job Description Work Arrangement: Dallas-based / Hybrid Visa Sponsorship: Not available. Candidates must already be authorized to work in the United States without current or future employer sponsorship. Job Summary We are seeking a highly experienced Senior MLOps Engineer with strong hands-on Snowflake experience to support enterprise machine learning platforms and production ML workloads. The ideal candidate has hands-on experience taking machine learning models from experimentation through production and building the deployment pipelines, monitoring, automation, infrastructure, and governance capabilities required to operate ML solutions reliably at enterprise scale. This role will work closely with Data Scientists, ML Engineers, Data Engineers, Cloud Engineers, and enterprise platform teams. Key Responsibilities Design, build, and maintain enterprise-grade MLOps platforms and pipelines. Operationalize machine learning models developed by Data Science teams. Build automated ML workflows covering training, validation, deployment, monitoring, retraining, and retirement. Implement CI/CD pipelines specifically for machine learning workloads. Establish model registry, versioning, lineage, artifact management, and reproducibility. Implement model monitoring, data drift detection, model drift detection, prediction-quality monitoring, and alerting. Integrate ML workloads with Snowflake-based enterprise data environments . Build and optimize Python- and SQL-based data and ML pipelines. Support Snowflake data ingestion, transformation, compute, security, and ML integrations. Containerize ML workloads using Docker and deploy workloads through Kubernetes or comparable orchestration platforms. Implement logging, observability, alerting, and production support processes. Automate deployment and infrastructure provisioning using modern DevOps and Infrastructure-as-Code practices. Support model governance, approval workflows, lineage, auditability, and access controls. Troubleshoot production ML pipelines, model-serving infrastructure, Snowflake integrations, and performance issues. Develop reusable MLOps frameworks, standards, templates, and best practices. Mandatory Qualifications Candidates must have hands-on production experience in both MLOps and Snowflake . MLOps - Required Strong production experience with: ML model deployment and operationalization Model lifecycle management ML CI/CD Experiment tracking Model registry and versioning Automated model validation Model monitoring Data and model drift detection Retraining pipelines Pipeline orchestration Production troubleshooting Experience with one or more of the following: ML flow Kubeflow AWS SageMaker Azure Machine Learning Airflow Argo Workflows Prefect Dagster Equivalent enterprise MLOps platforms Snowflake - Required Strong hands-on Snowflake experience including: Snowflake architecture Databases, schemas, tables, and views Virtual warehouses Compute management Snowflake security and RBAC Data ingestion and transformation Performance optimization Python integration Snowflake integration with ML pipelines Experience with the following is strongly preferred: Snowpark Snowpark Python Snowflake ML Snowflake Model Registry Snowflake Feature Store Snowflake Tasks and Streams Dynamic Tables Snowpipe Cortex / Snowflake AI capabilities Additional Required Technical Skills Strong Python Strong SQL Git REST APIs Linux Shell scripting Docker CI/CD Cloud platforms such as AWS, Azure, or GCP Preferred Skills Experience with: Kubernetes Terraform GitHub Actions Jenkins GitLab CI/CD Azure DevOps dbt Spark Kafka Grafana CloudWatch Evidently Education and Experience Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Machine Learning, or related field. 6+ years of software, cloud, data, or ML engineering experience. 3+ years of hands-on production MLOps experience. Strong hands-on Snowflake experience. Experience deploying ML models into production. Experience implementing ML CI/CD pipelines. Strong Python and SQL skills. Experience with Docker and cloud infrastructure. Work Authorization This position does not provide visa sponsorship. Candidates must be currently authorized to work in the United States without employer sponsorship and must not require sponsorship now or in the future. Company Description About KAPI Advisors LLC KAPI Advisors LLC is a forward-thinking boutique firm at the intersection of AI, Machine Learning, Data Analytics, Generative AI, Mathematical Optimization, and Cloud Platform Engineering. We build highly personalized, cutting-edge solutions tailored to the specific needs of each client - empowering organizations with powerful tools to unlock new business opportunities, operational efficiencies, and platform reliability at scale. At KAPI Advisors, we are passionate about solving complex, real-world challenges through technology. Our capabilities span intelligent agent-based systems, advanced data analytics, optimization algorithms, and robust cloud infrastructure - all designed to work together seamlessly. Our offerings include Generative AI systems that enable automation and intelligent decision-making, ML models that surface actionable insights, Mathematical Optimization techniques for supply chain management, resource allocation, and logistics, and Site Reliability Engineering practices that ensure the platforms powering these solutions remain performant, resilient, and production-ready. We believe that great AI and data products are only as strong as the infrastructure beneath them. That's why our SRE and DevOps practice is central to everything we build - from designing observability frameworks and incident response playbooks, to implementing chaos engineering, disaster recovery, and developer productivity tooling that reduces toil and accelerates delivery. As a boutique firm, we offer the agility and depth that larger organizations simply cannot match. Our team works directly with clients to understand their unique challenges and craft tailored strategies that deliver both immediate impact and long-term resilience. Whether you're looking to scale an AI platform, modernize your cloud infrastructure, or build the reliability engineering culture your engineering team deserves - KAPI Advisors is the partner built for it. Company Description About KAPI Advisors LLC KAPI Advisors LLC is a forward-thinking boutique firm at the intersection of AI, Machine Learning, Data Analytics, Generative AI, Mathematical Optimization, and Cloud Platform Engineering. We build highly personalized, cutting-edge solutions tailored to the specific needs of each client - empowering organizations with powerful tools to unlock new business opportunities, operational efficiencies, and platform reliability at scale. At KAPI Advisors, we are passionate about solving complex, real-world challenges through technology. Our capabilities span intelligent agent-based systems, advanced data analytics, optimization algorithms, and robust cloud infrastructure - all designed to work together seamlessly. Our offerings include Generative AI systems that enable automation and intelligent decision-making, ML models that surface actionable insights, Mathematical Optimization techniques for supply chain management, resource allocation, and logistics, and Site Reliability Engineering practices that ensure the platforms powering these solutions remain performant, resilient, and production-ready. We believe that great AI and data products are only as strong as the infrastructure beneath them. That's why our SRE and DevOps practice is central to everything we build - from designing observability frameworks and incident response playbooks, to implementing chaos engineering, disaster recovery, and developer productivity tooling that reduces toil and accelerates delivery. As a boutique firm, we offer the agility and depth that larger organizations simply cannot match. Our team works directly with clients to understand their unique challenges and craft tailored strategies that deliver both immediate impact and long-term resilience. Whether you're looking to scale an AI platform, modernize your cloud infrastructure, or build the reliability engineering culture your engineering team deserves - KAPI Advisors is the partner built for it.
Staff AI Engineer - Enterprise Analysis Platform (Remote Eligible) 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 Intelligent Foundations and Experiences (IFX) team is currently working on building a new AI native platform to empower our broader business community to execute AI assisted analysis across our many lines of business. We are building an AI native, at-scale (15,000+ users at destination), enterprise platform intertwining deterministic code with non-deterministic reasoning systems as well as both frontier and home grown AI models, to transform how our company works in the data analysis space. Capital One is open to hiring a Remote Employee for this opportunity. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One 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 trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or AI plus at least 8 years of experience developing AI and ML algorithms or technologies, or Master's degree plus at least 6 years of experience developing AI and ML algorithms or technologies At least 8 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Master's degree in Computer Science, Computer Engineering, or relevant technical field Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost 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 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): $244,700 - $279,200 for Distinguished AI Engineer Cambridge, MA: $269,100 - $307,200 for Distinguished AI Engineer McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer New York, NY: $293,600 - $335,100 for Distinguished AI Engineer San Francisco, CA: $293,600 - $335,100 for Distinguished AI Engineer San Jose, CA: $293,600 - $335,100 for Distinguished AI 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).
09/14/2026
Full time
Staff AI Engineer - Enterprise Analysis Platform (Remote Eligible) 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 Intelligent Foundations and Experiences (IFX) team is currently working on building a new AI native platform to empower our broader business community to execute AI assisted analysis across our many lines of business. We are building an AI native, at-scale (15,000+ users at destination), enterprise platform intertwining deterministic code with non-deterministic reasoning systems as well as both frontier and home grown AI models, to transform how our company works in the data analysis space. Capital One is open to hiring a Remote Employee for this opportunity. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One 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 trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or AI plus at least 8 years of experience developing AI and ML algorithms or technologies, or Master's degree plus at least 6 years of experience developing AI and ML algorithms or technologies At least 8 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Master's degree in Computer Science, Computer Engineering, or relevant technical field Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost 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 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): $244,700 - $279,200 for Distinguished AI Engineer Cambridge, MA: $269,100 - $307,200 for Distinguished AI Engineer McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer New York, NY: $293,600 - $335,100 for Distinguished AI Engineer San Francisco, CA: $293,600 - $335,100 for Distinguished AI Engineer San Jose, CA: $293,600 - $335,100 for Distinguished AI 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).
Senior Staff AI Engineer 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 Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. 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. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex enterprise AI systems Demonstrated ability to lead and mentor an engineering organization and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast 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 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. Cambridge, MA: $314,800 - $359,300 for Sr. Distinguished AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Distinguished AI Engineer New York, NY: $343,400 - $392,000 for Sr. Distinguished AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Distinguished AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Distinguished AI 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).
09/14/2026
Full time
Senior Staff AI Engineer 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 Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. 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. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex enterprise AI systems Demonstrated ability to lead and mentor an engineering organization and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast 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 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. Cambridge, MA: $314,800 - $359,300 for Sr. Distinguished AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Distinguished AI Engineer New York, NY: $343,400 - $392,000 for Sr. Distinguished AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Distinguished AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Distinguished AI 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).
Staff AI Engineer (Remote Eligible) 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 Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One 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 trailblazer 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 in Computer Science, Engineering, or AI plus at least 8 years of experience developing AI and ML algorithms or technologies, or Master's degree plus at least 6 years of experience developing AI and ML algorithms or technologies At least 8 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Master's degree in Computer Science, Computer Engineering, or relevant technical field Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost 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 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): $244,700 - $279,200 for Distinguished AI Engineer Cambridge, MA: $269,100 - $307,200 for Distinguished AI Engineer McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer New York, NY: $293,600 - $335,100 for Distinguished AI Engineer Richmond, VA: $244,700 - $279,200 for Distinguished AI Engineer San Francisco, CA: $293,600 - $335,100 for Distinguished AI Engineer San Jose, CA: $293,600 - $335,100 for Distinguished AI 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).
09/14/2026
Full time
Staff AI Engineer (Remote Eligible) 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 Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One 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 trailblazer 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 in Computer Science, Engineering, or AI plus at least 8 years of experience developing AI and ML algorithms or technologies, or Master's degree plus at least 6 years of experience developing AI and ML algorithms or technologies At least 8 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Master's degree in Computer Science, Computer Engineering, or relevant technical field Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost 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 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): $244,700 - $279,200 for Distinguished AI Engineer Cambridge, MA: $269,100 - $307,200 for Distinguished AI Engineer McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer New York, NY: $293,600 - $335,100 for Distinguished AI Engineer Richmond, VA: $244,700 - $279,200 for Distinguished AI Engineer San Francisco, CA: $293,600 - $335,100 for Distinguished AI Engineer San Jose, CA: $293,600 - $335,100 for Distinguished AI 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).
Staff AI Engineer role (Remote Eligible) 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 Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One Capital One is open to hiring a Remote Employee for this opportunity. 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 trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or AI plus at least 8 years of experience developing AI and ML algorithms or technologies, or Master's degree plus at least 6 years of experience developing AI and ML algorithms or technologies At least 8 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Master's degree in Computer Science, Computer Engineering, or relevant technical field Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost 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 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. Cambridge, MA: $269,100 - $307,200 for Distinguished AI Engineer McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer New York, NY: $293,600 - $335,100 for Distinguished AI Engineer Richmond, VA: $244,700 - $279,200 for Distinguished AI Engineer San Francisco, CA: $293,600 - $335,100 for Distinguished AI Engineer San Jose, CA: $293,600 - $335,100 for Distinguished AI 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).
09/14/2026
Full time
Staff AI Engineer role (Remote Eligible) 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 Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One Capital One is open to hiring a Remote Employee for this opportunity. 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 trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or AI plus at least 8 years of experience developing AI and ML algorithms or technologies, or Master's degree plus at least 6 years of experience developing AI and ML algorithms or technologies At least 8 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Master's degree in Computer Science, Computer Engineering, or relevant technical field Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost 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 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. Cambridge, MA: $269,100 - $307,200 for Distinguished AI Engineer McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer New York, NY: $293,600 - $335,100 for Distinguished AI Engineer Richmond, VA: $244,700 - $279,200 for Distinguished AI Engineer San Francisco, CA: $293,600 - $335,100 for Distinguished AI Engineer San Jose, CA: $293,600 - $335,100 for Distinguished AI 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).
Staff AI Engineer role (Remote Eligible) 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 Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One Capital One is open to hiring a Remote Employee for this opportunity. 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 trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or AI plus at least 8 years of experience developing AI and ML algorithms or technologies, or Master's degree plus at least 6 years of experience developing AI and ML algorithms or technologies At least 8 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Master's degree in Computer Science, Computer Engineering, or relevant technical field Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost 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 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. Cambridge, MA: $269,100 - $307,200 for Distinguished AI Engineer McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer New York, NY: $293,600 - $335,100 for Distinguished AI Engineer Richmond, VA: $244,700 - $279,200 for Distinguished AI Engineer San Francisco, CA: $293,600 - $335,100 for Distinguished AI Engineer San Jose, CA: $293,600 - $335,100 for Distinguished AI 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).
09/14/2026
Full time
Staff AI Engineer role (Remote Eligible) 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 Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One Capital One is open to hiring a Remote Employee for this opportunity. 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 trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or AI plus at least 8 years of experience developing AI and ML algorithms or technologies, or Master's degree plus at least 6 years of experience developing AI and ML algorithms or technologies At least 8 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Master's degree in Computer Science, Computer Engineering, or relevant technical field Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost 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 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. Cambridge, MA: $269,100 - $307,200 for Distinguished AI Engineer McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer New York, NY: $293,600 - $335,100 for Distinguished AI Engineer Richmond, VA: $244,700 - $279,200 for Distinguished AI Engineer San Francisco, CA: $293,600 - $335,100 for Distinguished AI Engineer San Jose, CA: $293,600 - $335,100 for Distinguished AI 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).
Staff AI Engineer Job Description 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 Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. 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. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies At least 8 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast 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 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. Cambridge, MA: $269,100 - $307,200 for Distinguished AI Engineer McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer New York, NY: $293,600 - $335,100 for Distinguished AI Engineer San Francisco, CA: $293,600 - $335,100 for Distinguished AI Engineer San Jose, CA: $293,600 - $335,100 for Distinguished AI 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).
09/14/2026
Full time
Staff AI Engineer Job Description 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 Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. 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. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies At least 8 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast 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 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. Cambridge, MA: $269,100 - $307,200 for Distinguished AI Engineer McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer New York, NY: $293,600 - $335,100 for Distinguished AI Engineer San Francisco, CA: $293,600 - $335,100 for Distinguished AI Engineer San Jose, CA: $293,600 - $335,100 for Distinguished AI 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).
Staff AI Engineer Job Description 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 Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. 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. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies At least 8 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast 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 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. Cambridge, MA: $269,100 - $307,200 for Distinguished AI Engineer McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer New York, NY: $293,600 - $335,100 for Distinguished AI Engineer San Francisco, CA: $293,600 - $335,100 for Distinguished AI Engineer San Jose, CA: $293,600 - $335,100 for Distinguished AI 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).
09/14/2026
Full time
Staff AI Engineer Job Description 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 Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. 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. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies At least 8 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast 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 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. Cambridge, MA: $269,100 - $307,200 for Distinguished AI Engineer McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer New York, NY: $293,600 - $335,100 for Distinguished AI Engineer San Francisco, CA: $293,600 - $335,100 for Distinguished AI Engineer San Jose, CA: $293,600 - $335,100 for Distinguished AI 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).
Job Description Job Description Work Arrangement: Dallas-based / Hybrid Visa Sponsorship: Not available. Candidates must already be authorized to work in the United States without current or future employer sponsorship. Job Summary We are seeking a highly experienced Senior MLOps Engineer with strong hands-on Snowflake experience to support enterprise machine learning platforms and production ML workloads. The ideal candidate has hands-on experience taking machine learning models from experimentation through production and building the deployment pipelines, monitoring, automation, infrastructure, and governance capabilities required to operate ML solutions reliably at enterprise scale. This role will work closely with Data Scientists, ML Engineers, Data Engineers, Cloud Engineers, and enterprise platform teams. Key Responsibilities Design, build, and maintain enterprise-grade MLOps platforms and pipelines. Operationalize machine learning models developed by Data Science teams. Build automated ML workflows covering training, validation, deployment, monitoring, retraining, and retirement. Implement CI/CD pipelines specifically for machine learning workloads. Establish model registry, versioning, lineage, artifact management, and reproducibility. Implement model monitoring, data drift detection, model drift detection, prediction-quality monitoring, and alerting. Integrate ML workloads with Snowflake-based enterprise data environments . Build and optimize Python- and SQL-based data and ML pipelines. Support Snowflake data ingestion, transformation, compute, security, and ML integrations. Containerize ML workloads using Docker and deploy workloads through Kubernetes or comparable orchestration platforms. Implement logging, observability, alerting, and production support processes. Automate deployment and infrastructure provisioning using modern DevOps and Infrastructure-as-Code practices. Support model governance, approval workflows, lineage, auditability, and access controls. Troubleshoot production ML pipelines, model-serving infrastructure, Snowflake integrations, and performance issues. Develop reusable MLOps frameworks, standards, templates, and best practices. Mandatory Qualifications Candidates must have hands-on production experience in both MLOps and Snowflake . MLOps - Required Strong production experience with: ML model deployment and operationalization Model lifecycle management ML CI/CD Experiment tracking Model registry and versioning Automated model validation Model monitoring Data and model drift detection Retraining pipelines Pipeline orchestration Production troubleshooting Experience with one or more of the following: ML flow Kubeflow AWS SageMaker Azure Machine Learning Airflow Argo Workflows Prefect Dagster Equivalent enterprise MLOps platforms Snowflake - Required Strong hands-on Snowflake experience including: Snowflake architecture Databases, schemas, tables, and views Virtual warehouses Compute management Snowflake security and RBAC Data ingestion and transformation Performance optimization Python integration Snowflake integration with ML pipelines Experience with the following is strongly preferred: Snowpark Snowpark Python Snowflake ML Snowflake Model Registry Snowflake Feature Store Snowflake Tasks and Streams Dynamic Tables Snowpipe Cortex / Snowflake AI capabilities Additional Required Technical Skills Strong Python Strong SQL Git REST APIs Linux Shell scripting Docker CI/CD Cloud platforms such as AWS, Azure, or GCP Preferred Skills Experience with: Kubernetes Terraform GitHub Actions Jenkins GitLab CI/CD Azure DevOps dbt Spark Kafka Grafana CloudWatch Evidently Education and Experience Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Machine Learning, or related field. 6+ years of software, cloud, data, or ML engineering experience. 3+ years of hands-on production MLOps experience. Strong hands-on Snowflake experience. Experience deploying ML models into production. Experience implementing ML CI/CD pipelines. Strong Python and SQL skills. Experience with Docker and cloud infrastructure. Work Authorization This position does not provide visa sponsorship. Candidates must be currently authorized to work in the United States without employer sponsorship and must not require sponsorship now or in the future. Company Description About KAPI Advisors LLC KAPI Advisors LLC is a forward-thinking boutique firm at the intersection of AI, Machine Learning, Data Analytics, Generative AI, Mathematical Optimization, and Cloud Platform Engineering. We build highly personalized, cutting-edge solutions tailored to the specific needs of each client - empowering organizations with powerful tools to unlock new business opportunities, operational efficiencies, and platform reliability at scale. At KAPI Advisors, we are passionate about solving complex, real-world challenges through technology. Our capabilities span intelligent agent-based systems, advanced data analytics, optimization algorithms, and robust cloud infrastructure - all designed to work together seamlessly. Our offerings include Generative AI systems that enable automation and intelligent decision-making, ML models that surface actionable insights, Mathematical Optimization techniques for supply chain management, resource allocation, and logistics, and Site Reliability Engineering practices that ensure the platforms powering these solutions remain performant, resilient, and production-ready. We believe that great AI and data products are only as strong as the infrastructure beneath them. That's why our SRE and DevOps practice is central to everything we build - from designing observability frameworks and incident response playbooks, to implementing chaos engineering, disaster recovery, and developer productivity tooling that reduces toil and accelerates delivery. As a boutique firm, we offer the agility and depth that larger organizations simply cannot match. Our team works directly with clients to understand their unique challenges and craft tailored strategies that deliver both immediate impact and long-term resilience. Whether you're looking to scale an AI platform, modernize your cloud infrastructure, or build the reliability engineering culture your engineering team deserves - KAPI Advisors is the partner built for it. Company Description About KAPI Advisors LLC KAPI Advisors LLC is a forward-thinking boutique firm at the intersection of AI, Machine Learning, Data Analytics, Generative AI, Mathematical Optimization, and Cloud Platform Engineering. We build highly personalized, cutting-edge solutions tailored to the specific needs of each client - empowering organizations with powerful tools to unlock new business opportunities, operational efficiencies, and platform reliability at scale. At KAPI Advisors, we are passionate about solving complex, real-world challenges through technology. Our capabilities span intelligent agent-based systems, advanced data analytics, optimization algorithms, and robust cloud infrastructure - all designed to work together seamlessly. Our offerings include Generative AI systems that enable automation and intelligent decision-making, ML models that surface actionable insights, Mathematical Optimization techniques for supply chain management, resource allocation, and logistics, and Site Reliability Engineering practices that ensure the platforms powering these solutions remain performant, resilient, and production-ready. We believe that great AI and data products are only as strong as the infrastructure beneath them. That's why our SRE and DevOps practice is central to everything we build - from designing observability frameworks and incident response playbooks, to implementing chaos engineering, disaster recovery, and developer productivity tooling that reduces toil and accelerates delivery. As a boutique firm, we offer the agility and depth that larger organizations simply cannot match. Our team works directly with clients to understand their unique challenges and craft tailored strategies that deliver both immediate impact and long-term resilience. Whether you're looking to scale an AI platform, modernize your cloud infrastructure, or build the reliability engineering culture your engineering team deserves - KAPI Advisors is the partner built for it.
09/13/2026
Full time
Job Description Job Description Work Arrangement: Dallas-based / Hybrid Visa Sponsorship: Not available. Candidates must already be authorized to work in the United States without current or future employer sponsorship. Job Summary We are seeking a highly experienced Senior MLOps Engineer with strong hands-on Snowflake experience to support enterprise machine learning platforms and production ML workloads. The ideal candidate has hands-on experience taking machine learning models from experimentation through production and building the deployment pipelines, monitoring, automation, infrastructure, and governance capabilities required to operate ML solutions reliably at enterprise scale. This role will work closely with Data Scientists, ML Engineers, Data Engineers, Cloud Engineers, and enterprise platform teams. Key Responsibilities Design, build, and maintain enterprise-grade MLOps platforms and pipelines. Operationalize machine learning models developed by Data Science teams. Build automated ML workflows covering training, validation, deployment, monitoring, retraining, and retirement. Implement CI/CD pipelines specifically for machine learning workloads. Establish model registry, versioning, lineage, artifact management, and reproducibility. Implement model monitoring, data drift detection, model drift detection, prediction-quality monitoring, and alerting. Integrate ML workloads with Snowflake-based enterprise data environments . Build and optimize Python- and SQL-based data and ML pipelines. Support Snowflake data ingestion, transformation, compute, security, and ML integrations. Containerize ML workloads using Docker and deploy workloads through Kubernetes or comparable orchestration platforms. Implement logging, observability, alerting, and production support processes. Automate deployment and infrastructure provisioning using modern DevOps and Infrastructure-as-Code practices. Support model governance, approval workflows, lineage, auditability, and access controls. Troubleshoot production ML pipelines, model-serving infrastructure, Snowflake integrations, and performance issues. Develop reusable MLOps frameworks, standards, templates, and best practices. Mandatory Qualifications Candidates must have hands-on production experience in both MLOps and Snowflake . MLOps - Required Strong production experience with: ML model deployment and operationalization Model lifecycle management ML CI/CD Experiment tracking Model registry and versioning Automated model validation Model monitoring Data and model drift detection Retraining pipelines Pipeline orchestration Production troubleshooting Experience with one or more of the following: ML flow Kubeflow AWS SageMaker Azure Machine Learning Airflow Argo Workflows Prefect Dagster Equivalent enterprise MLOps platforms Snowflake - Required Strong hands-on Snowflake experience including: Snowflake architecture Databases, schemas, tables, and views Virtual warehouses Compute management Snowflake security and RBAC Data ingestion and transformation Performance optimization Python integration Snowflake integration with ML pipelines Experience with the following is strongly preferred: Snowpark Snowpark Python Snowflake ML Snowflake Model Registry Snowflake Feature Store Snowflake Tasks and Streams Dynamic Tables Snowpipe Cortex / Snowflake AI capabilities Additional Required Technical Skills Strong Python Strong SQL Git REST APIs Linux Shell scripting Docker CI/CD Cloud platforms such as AWS, Azure, or GCP Preferred Skills Experience with: Kubernetes Terraform GitHub Actions Jenkins GitLab CI/CD Azure DevOps dbt Spark Kafka Grafana CloudWatch Evidently Education and Experience Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Machine Learning, or related field. 6+ years of software, cloud, data, or ML engineering experience. 3+ years of hands-on production MLOps experience. Strong hands-on Snowflake experience. Experience deploying ML models into production. Experience implementing ML CI/CD pipelines. Strong Python and SQL skills. Experience with Docker and cloud infrastructure. Work Authorization This position does not provide visa sponsorship. Candidates must be currently authorized to work in the United States without employer sponsorship and must not require sponsorship now or in the future. Company Description About KAPI Advisors LLC KAPI Advisors LLC is a forward-thinking boutique firm at the intersection of AI, Machine Learning, Data Analytics, Generative AI, Mathematical Optimization, and Cloud Platform Engineering. We build highly personalized, cutting-edge solutions tailored to the specific needs of each client - empowering organizations with powerful tools to unlock new business opportunities, operational efficiencies, and platform reliability at scale. At KAPI Advisors, we are passionate about solving complex, real-world challenges through technology. Our capabilities span intelligent agent-based systems, advanced data analytics, optimization algorithms, and robust cloud infrastructure - all designed to work together seamlessly. Our offerings include Generative AI systems that enable automation and intelligent decision-making, ML models that surface actionable insights, Mathematical Optimization techniques for supply chain management, resource allocation, and logistics, and Site Reliability Engineering practices that ensure the platforms powering these solutions remain performant, resilient, and production-ready. We believe that great AI and data products are only as strong as the infrastructure beneath them. That's why our SRE and DevOps practice is central to everything we build - from designing observability frameworks and incident response playbooks, to implementing chaos engineering, disaster recovery, and developer productivity tooling that reduces toil and accelerates delivery. As a boutique firm, we offer the agility and depth that larger organizations simply cannot match. Our team works directly with clients to understand their unique challenges and craft tailored strategies that deliver both immediate impact and long-term resilience. Whether you're looking to scale an AI platform, modernize your cloud infrastructure, or build the reliability engineering culture your engineering team deserves - KAPI Advisors is the partner built for it. Company Description About KAPI Advisors LLC KAPI Advisors LLC is a forward-thinking boutique firm at the intersection of AI, Machine Learning, Data Analytics, Generative AI, Mathematical Optimization, and Cloud Platform Engineering. We build highly personalized, cutting-edge solutions tailored to the specific needs of each client - empowering organizations with powerful tools to unlock new business opportunities, operational efficiencies, and platform reliability at scale. At KAPI Advisors, we are passionate about solving complex, real-world challenges through technology. Our capabilities span intelligent agent-based systems, advanced data analytics, optimization algorithms, and robust cloud infrastructure - all designed to work together seamlessly. Our offerings include Generative AI systems that enable automation and intelligent decision-making, ML models that surface actionable insights, Mathematical Optimization techniques for supply chain management, resource allocation, and logistics, and Site Reliability Engineering practices that ensure the platforms powering these solutions remain performant, resilient, and production-ready. We believe that great AI and data products are only as strong as the infrastructure beneath them. That's why our SRE and DevOps practice is central to everything we build - from designing observability frameworks and incident response playbooks, to implementing chaos engineering, disaster recovery, and developer productivity tooling that reduces toil and accelerates delivery. As a boutique firm, we offer the agility and depth that larger organizations simply cannot match. Our team works directly with clients to understand their unique challenges and craft tailored strategies that deliver both immediate impact and long-term resilience. Whether you're looking to scale an AI platform, modernize your cloud infrastructure, or build the reliability engineering culture your engineering team deserves - KAPI Advisors is the partner built for it.