22 jobs found

Job Description Job Description Senior Data Analyst Req ID 003-25 v1.0 HazeGrayCyber, LLC is focused on delivering Cyber Security and Zero Trust Solutions to the US National Defense community and our allies and partners. This position will provide Information and Task Management Support to MCICOM, G-9, and the Marine Corps. Location: Performance will take place at both the Government's facility and the contractor's facility. Travel will be required to conduct on-site IA tasks at Marine Corps Regions/Installations Responsibilities: High-level problem solver who uses advanced techniques, such as optimization, data mining, statistical analysis and mathematical modeling; develop solutions to help organizations operate more efficiently and cost-effectively. Perform analysis applying appropriate scientific processes and modeling techniques; conduct research initiatives and contribute to data analysis initiatives; apply operations research methodology to various forms of analyses; present information into meaningful reports and presentation material; interprets information that may assist management with decision making and/or policy formulation. Specifically - working in partnership with a Senior Data Scientist and Senior Data Analyst. Collect and normalize data, analyze, and present results of enterprise to individual real property assets or MCICOM Marine Corps programs within the installations portfolios and functions, and provide programmatic, cost, budget, schedule, and technical requirements utilizing descriptive methods, tools, and supporting visualizations. Use analytic tools to combine, analyze, and interpret very large and complex datasets to perform exploratory analyses and develop data-informed organizational solutions. Design, develop, enhance, and support new and existing dashboards and visualizations using the following tools, but not limited to PowerPoint, Tableau, Python, or R to support planning, programming, budget, and execution decisions. Conduct predictive analysis and refine/update models to forecast future infrastructure and installation services requirements and resources to support the Marine Corps Future Force, tenant requirements, and families. Use of operations research techniques and methods, machine learning models, and other predictive analytics tools to identify trends, patterns, and potential future outcomes. Refine the predictive infrastructure model that focuses on lifecycle management including incorporating known funding levels, known facility investment plans (supportive of military construction (both new mission/footprint and recapitalization), restoration and modernization, sustainment, and demolition requirements) and incorporating the Marine Corps' Facility Investment Strategy (FIS). Provide recommendations of optimal investment strategies to support the infrastructure and installation services portfolios. This analysis will include optimization models implementing known or projected investment goals, scenario planning, and the integration of various budgets, real property, and input data (to include but not limited to inflation, metrics, and factors) to support actionable investment recommendations over the Future Years Defense Program (FYDP). Deploy descriptive, predictive and prescriptive infrastructure model into government environment and develop training materials and train government personnel at the Regions/ Installations for use. The following steps outline a Full Enterprise, Readiness Model that meets Full Operational Capability (FOC) to include using advanced analytic software or leverage a Large Language Model (LLM). Build prescriptive infrastructure model in the Government (OSD Advana) Cloud Environment Required Education and Experience 10+ years of experience and BA/BS degree in data science, computer science, engineering, mathematics, operations research or another technical field of study or 5+ years of experience and MA/MS degree in data science, computer science, engineering, mathematics, operations research or another technical field of study Desired Education and Experience 20+ years of specialized experience and a BA/MS degree in data science, computer science, engineering, mathematics, operations research or another technical field of study with expert knowledge of databases, data modeling, and SQL PhD in Operations Research Desired Certifications International Cost Estimating & Analysis Association (ICEAA) Certification Security US Citizenship Required Ability to obtain and maintain a Government Secret Security Clearance Overseas Performance Requirements Overseas performance and/or travel may be required in Japan, Korea, and/or Guam. NOTE: SPOT requirements will require the use of SPOT for approving SOFA status. HazeGrayCyber, LLC is an Equal Opportunity Employer with a strong commitment to supporting and retaining a diverse and talented workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability. HazeGrayCyber, LLC offers competitive compensation and benefits as well as great long-term career opportunities. For more information or to apply, visit our website at

Job Description Job Description Job Description ACTIVE SECURITY CLEARANCE AT THE TS/SCI POLYGRAPH LEVEL IS REQUIRED Are you a powerhouse data scientist who thrives on solving large-scale operational challenges? Bring your 10+ years of advanced expertise to architect predictive models, run complex simulations, and drive multi-objective decision frameworks using Pandas, R, Python, or MATLAB. Translate intricate machine learning and statistical data analytics into clear strategic narratives for high-level stakeholders! In this role, you will lead the charge in defining complex problems, gathering critical stakeholder requirements, and applying advanced mathematical techniques to guide critical decision-making. If you are ready to transform large-scale operational challenges into optimized mission solutions alongside a team that values engineering excellence, let's achieve more together! The annual base salary range for this role is $200,000-$237,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things. , Required Skills Core Experience: 10+ years of professional experience analyzing complex management and operational problems using advanced operations research techniques. Modeling Simulation: 4+ years of hands-on experience applying modeling and simulation frameworks to address high-level decision analysis problems. Strategic Analysis: 4+ years of experience conducting multi-objective decision analysis or cost-benefit analysis in direct support of research objectives. Data Toolset Toolkits: 4+ years of deep expertise using tools and libraries such as Pandas, R, Excel/VBA, Arena, Octave, Tableau, Gurobi, CPLEX, ExtendSim, SAS, Netica, Statsmodels, Stata, MATLAB, or SPSS. Stakeholder Engagement: Proven experience conducting problem definitions and gathering detailed data requirements directly from stakeholders. Communication: Outstanding oral and written communication skills with a track record of explaining intricate data analysis to non-technical stakeholders. Education: 10 years of experience with a technical bachelor's degree, 14+ years of experience without a techncial bachelor's degree. , Desired Skills Model Validation: Experience developing and performing rigorous verification and validation (VV) of models to ensure adequacy and performance. Knowledge Sharing: Experience developing and delivering comprehensive training materials for operations research techniques. Executive Briefing: Experience briefing high-level results and preparing thorough written reports on analytic approaches and methodologies. Emerging Tech: Familiarity or experience with machine learning and large language models (LLMs) to solve complex enterprise problems. , About Nyla Technology Solutions Nyla Technology Solutions delivers exceptional Artificial Intelligence (AI), Data Science, and Software Engineering services for the U.S. Government. Nyla embraces a forward-thinking and bold approach at every turn, earning us a solid reputation of technical trendsetters within the industry. We have a passion for developing solutions that have a quick and immediate impact on mission. Headquartered in Columbia, Maryland, our customers love how we tackle their most challenging problems and get things done. If you have the unique experience and expertise we are seeking, along with the desire and determination to invest your time and energy as a part of Nyla's team, Taking Care of All of You Nyla provides a top-of-market compensation and benefits package. And through our unique Nyla FLEX program, we custom tailor these benefits to best fit your lifestyle. The Nyla FLEX benefit program is designed to offer you flexibility in the 3 biggest areas of your life: your pay, your leave, and your schedule. PAY - Nyla starts with 4 weeks of Annual Leave plus 11 holidays and an additional day of Annual Leave for each year you're at the company. You have the flexibility to cash out your annual leave hours, opt out of other Nyla benefits, and/or arrange for additional hours on contract (over 40 hrs/week). There's even an option to earn 1.3 times your hourly rate once you work over 1880 hours on contract! LEAVE - Want to spend more time with the family? Want more time to travel the world? You can BUY additional annual leave for a total of 6 weeks of annual leave. That's up to 240 hours of leave plus 11 holidays! That's not even including paid anniversary leave! SCHEDULE - Does the traditional 40-hour workweek no longer fit your lifestyle? With Nyla FLEX, you have the freedom to scale down to 30-32 hours while still enjoying the top-notch Nyla benefits you know and love. It's flexibility that works for you without compromising the perks! WHAT ABOUT OTHER BENEFITS? Nyla's health care (medical, dental, and vision) is 100% covered by the company. We provide 10% 401k matching - with full vesting day 1! Our Professional Development offers $5,000 per year to be used towards fees, tuition, or time off for your continued growth. We even have a student loan repayment program and we provide 8 hours of volunteering annually so you can support your community, making your world a better place. To learn more about Nyla's culture and our exceptional benefit packages click here. Nyla is an equal opportunity employer.

Global Partners LP, a leading diversified energy company, seeks a Senior Director, Data Engineering to shape and execute our enterprise data strategy. Reporting into IT & Data Management, you will lead a team building scalable pipelines, warehouses, and platforms that power analytics, optimize fuel distribution, and support safe, reliable operations across our terminals and gas stations. You'll drive cloud data modernization, governance, and data quality, partnering with leaders across the business in a collaborative, safety- and integrity-focused culture. Responsibilities Define and lead the enterprise data engineering strategy for Global Partners LP. Oversee design and operation of scalable data pipelines, warehouses, and lakehouses. Partner with IT, logistics, and business leaders to enable analytics and optimization of fuel distribution and terminal operations. Establish data governance, quality, and security standards aligned to safety and regulatory needs. Lead and mentor a high-performing data engineering team and manage vendor partners. Drive adoption of modern cloud data platforms and advanced planning tools. Collaborate with data scientists and analysts to deliver trusted, timely data products. Align data engineering roadmap with corporate strategy and innovation initiatives. Required Skills Data engineering architecture Cloud data platforms (AWS/Azure/GCP) ETL/ELT pipeline design Data warehousing and lakehouse design SQL and distributed data processing (e.g., Spark) Data governance and data quality Real-time and batch data integration Team and portfolio leadership Stakeholder and executive communication Analytics and BI enablement

We are looking for an experienced and driven Senior Data Scientist to join our team and lead the development of AI-powered solutions. As a Senior Data Scientist, you will work closely with teams to design, implement, and deploy data-driven solutions that drive business value. You will help shape our data science strategy, mentor junior team members, and ensure the robustness and scalability of our models in production environments. What you'll need to bring to the role & Experian A Bachelor's/Master's/Ph.D. degree in computer science, Statistics, Mathematics, Data Science, or a related field. 5+ years of experience in data science or machine learning, with a strong track record of delivering impactful solutions. Proficiency in Python and ML frameworks such as scikit-learn, XGBoost, PyTorch, TensorFlow, or similar. Experience with statistical modeling, time series forecasting, supervised and unsupervised learning, and optimization techniques. Experience with generative AI principles. Intermediate to fluent English proficiency technical concepts clearly in English is essential. Experience working with financial datasets (e.g., credit scoring, fraud detection, risk modeling, pricing, or forecasting). Proficiency in SQL and experience with relational and non-relational databases (e.g., PostgreSQL, CosmosDB, MongoDB). Experience deploying models into production using Databricks and cloud platforms (AWS, GCP, or Azure). Familiarity with MLOps practices, CI/CD pipelines, and model monitoring tools. Experience with data visualization tools (e.g., Plotly, Tableau) to communicate insights effectively. Work that matters - What you'll be doing Lead the design, development, and deployment of machine learning models to solve high-impact financial problems. Collaborate with product managers, engineers, and business stakeholders to define data science use cases and translate them into actionable solutions. Analyse large-scale structured and unstructured datasets to extract insights and build predictive models. Develop and maintain robust model training workflows. Ensure model interpretability, fairness, and compliance with regulatory standards. Mentor junior data scientists and contribute to the growth of the data science team. Communicate findings and recommendations clearly to both technical and non-technical audiences. More about you Passion for using data to drive decisions. A mindset for continuous learning and innovation. Ethical awareness of bias, fairness, and transparency in AI models. Why this role is important to us This role is critical to our mission of leveraging data and AI to drive innovation across our services. As a Senior Data Scientist, your expertise will directly influence strategic decisions, improve customer outcomes, and enhance operational efficiency. You will collaborate closely with professionals from diverse backgrounds - including product, engineering, operations, and business strategy - to solve real-world challenges across multiple domains. Your insights will help shape our data science roadmap and deliver measurable value to the organization.

Job Description Job Description Company Description The Bosch Research and Technology Center North America with offices in Sunnyvale, California, Pittsburgh, Pennsylvania, and Cambridge, Massachusetts is a part of the global Bosch Group (), a company with over 70 billion euro revenue, 400,000 employees worldwide, a very diverse product portfolio, and a history spanning over 125 years. The Research and Technology Center North America (RTC-NA) is dedicated to providing technologies and system solutions for various Bosch business fields, primarily in the field of artificial intelligence, energy technologies, internet technologies, circuit design, semiconductors and wireless, as well as advanced MEMS design. As a part of the global research, our AI research in Silicon Valley focuses on Foundation Models, Natural Language Processing, Computer Vision & Mixed Reality, Cloud Robotics, Big Data Visual Analytics, Explainable AI (XAI), Data Science, AI System Engineering, Time-series Analysis. We develop scalable, intelligent, and trustworthy AIoT solutions for Bosch products and services in application areas such as automated driving, advanced driver assistance systems (ADAS), robotics, smart manufacturing, enterprise AI, health care, smart home and building solutions. Originating from the AI research in Silicon Valley, our Foundation Model Powered AI Enablers group plays a pivotal role in shaping the future of industrial AI experiences for Bosch products and services. By fusing cutting-edge machine learning, data analysis, and interactive visualization technologies, we research and develop scalable and transparent AI & big data analytic solutions (e.g., audio, images, sensor logs) for a range of domains, including Industry 4.0 (I4.0), IoT, autonomous driving, and connected vehicles. Our award-winning team (IEEE VIS best paper & best paper runner-ups) actively collaborates with leading academic and industry groups to advance research ideas and disseminate findings in top AI conferences and journals, such as CVPR, ICCV, ICRA, ECCV, NeurIPS, ICLR, SIGGRAPH, TVCG. Job Description Job Responsibilites: Develop and lead research of AI projects that label, predict, classify, cluster, describe and fuse multi-sensor data (including acoustic, telemetry timeseries signals, vibration, radar, lidar, image, Wi-Fi, and ultrasound data), to improve / enable advance driver assistance system (ADAS) functionality in vehicles and AI functionalities in other Bosch products. Architect, design and validate multi-modal deep learning and Timeseries Foundation Models (TSFM) to work with multivariate time series signals. Must have a grasp of both low and high frequency models. Integrate and extend timeseries models to leverage information from other auxiliary modalities such as videos and images to enhance context understanding. Offer expert insights to the management team in relevant technology sectors, aiding in strategic planning, R&D trajectory, and investment decisions. Stay abreast of the latest technological innovations, document and disseminate research findings through high-caliber publications and/or patent submissions. Qualifications Basic Qualifications Ph.D. in Computer Science, Electrical Engineering, Information Technology or a related discipline OR Masters degree with 2-3 years of preferred professional experience Expertise with Time Series FMs (beyond the time series task of forecasting) In-depth experience in signal processing for sensor data and their integration with deep-learning methods Proficiency in Python, PyTorch (including libraries such as torchaudio, torchvision, torchmetrics), familiarity with PyTorch Lightning A strong publication record in relevant venues such as ICASSP, NeurIPS, InterSpeech, ICML, ICLR, KDD, ICRA, CVPR, ICCV, ECCV or equivalent contributions to the field such as patents or significant open-source projects Strong interpersonal, communication, and teamwork capabilities Preferred Qualifications 3+ years of experience in industrial research Experience with one or more of the following areas: data-centric AI, synthetic data generation, agentic AI Proficiency with version control systems (Git), integrated development environment (VSCode or PyCharm) and experience with experiment tracking tools (MLFlow) Familiarity with high-performance computing systems and job schedulers (Slurm, LSF) Hands-on experience in product development in the above-mentioned areas for consumer/enterprise markets Experience leading projects with small teams, demonstrating the ability to mentor junior researchers and interns, manage project timelines, and deliver results within time constraints Additional Information Your well-being matters at Bosch! We offer a competitive compensation and a benefits package designed to empower you in every area of your life. This includes premium health coverage, a 401(k) with generous matching, resources for financial planning and goal setting, ample paid time off, parental leave, and comprehensive life and disability protection. We're investing in your success! Equal Opportunity Employer, including disability / veterans Bosch adheres to Federal, State, and Local laws regarding drug-testing. Employment is contingent upon the successful completion of a drug screen and background check. Candidates who have been offered the position must pass both screenings before their start date. The U.S. base salary range for this full-time position is $165,000 - $ 195,000. Within the range, individual pay is determined based on several factors, including, but not limited to, work experience and job knowledge, complexity of the role, job location, etc. Your Recruiter can share more details about the specific salary range for this position during the interview process.

Job Description Job Description Job Description Our client, a Los Angeles based financial services Company, is hiring for an experienced Assistant Vice President, Risk Analytics to join their Risk and Credit Group. The primary function of this role is to act as a Data Scientist for the Risk Management Department , and a Project Manager/Liaison for all related Risk systems and IT functions. You will need to design SQL queries and relational databases to carry out daily tasks and automate reports for the risk management department. Responsibilities will include, but are not limited to: Build, monitor, distribute risk reports and margin calculations Design SQL query and relational databases to carry out daily tasks and automate reports Create and Manage risk dashboards Perform complex data analysis on account balances and positions across the firm Manage ad hoc projects as requested by leadership Be the system administrator and point of contact for various risk systems and tools Present and explain analysis in a non-technical and accessible manner alongside data visualization Perform other tasks and duties as required and assigned Experience and Skills Bachelor's Degree from an accredited University, preferably in Computer Science, Data Science, or related field Advanced proficiency in SQL and understanding of data access tools 5+ years' experience in Information Technology, preferably for a financial services firm 5+ years' experience in Data Analytics, Risk Analysis, or related role Understanding of Equities, Options, and Margin is a plus Must be detail oriented and maintain data integrity Creative, solution-oriented mindset with the ability to handle pressure to meet deadlines Able to work with minimal supervision, taking ownership of work and completing tasks in timely manner, while adapting rapidly to changing work environments, priorities and organizational needs Ability to identify gaps in existing processes and gain efficiency through automation. Experience working with multiple teams across different time zones

Job Description Job Description Founded in 2012, H2O.ai is on a mission to democratize AI. As the world's leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built GenAI applications on their private data. With a focus on Sovereign AI-secure, compliant, and infrastructure-flexible deployments-H2O.ai delivers solutions that align with the highest standards of data privacy and control. Our open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Chipotle, Workday, Progressive Insurance, and NIH. H2O.ai partners include NVIDIA, Dell Technologies, Deloitte, Ernst & Young (EY), Snowflake, AWS, Google Cloud Platform (GCP), VAST Data and MinIO. H2O.ai's AI for Good program supports nonprofit groups, foundations, and communities in advancing education, healthcare, and environmental conservation. With a vibrant community of 2 million data scientists worldwide, H2O.ai aims to co-create valuable AI applications for all users. H2O.ai has raised 256 million from investors, including Commonwealth Bank, NVIDIA, Goldman Sachs, Wells Fargo, Capital One, Nexus Ventures and New York Life. For more information, visit . About This Opportunity We are looking for a Principal AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one. You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes. This position is based in Dallas, Texas and requires onsite customer interfacing. What You Will Do Customer Engagement Leadership Lead end-to-end technical engagement with enterprise customers, acting as the senior point of accountability for delivery quality, stakeholder relationships, and outcomes. Manage multiple concurrent engagement streams simultaneously - coordinating workplans, resourcing, and milestones across cross-functional teams. Serve as the primary technical escalation point for customer issues, proactively identifying risks and driving resolution across engineering, product, and leadership. Build and maintain trusted relationships with customer data science teams, engineering leads, and executive stakeholders - translating business needs into technical direction and back again. Lead pre-sales and proof-of-concept engagements, setting the technical strategy and ensuring the team delivers demonstrations that build genuine enterprise trust. Represent H2O.ai externally at customer workshops, executive briefings, and technical deep-dives as a credible senior voice. Agentic AI & LLM Engineering Design and build agentic AI systems and multi-agent frameworks that automate complex, multi-step enterprise workflows. Develop and deploy LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use. Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. Stay current with the rapidly evolving agentic AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best into customer engagements. End-to-End AI Application Development Own the full development lifecycle across multiple streams: from problem framing and data exploration through model development, API integration, and production deployment. Build scalable backend services and APIs that expose AI capabilities to enterprise applications and workflows. Integrate AI models into customer environments - cloud, on-prem, and hybrid - ensuring performance, stability, and maintainability at scale. Develop ML pipelines and LLMOps infrastructure that support continuous model improvement and monitoring in production. Team Collaboration & Delivery Excellence Coordinate delivery across engineers, program managers, and solution architects - ensuring workstreams are aligned, unblocked, and progressing to plan. Set the technical bar for the engagements you lead, reviewing outputs, shaping architecture decisions, and ensuring engineering quality across the team. Mentor and guide junior ML engineers and solution engineers within engagements, building team capability alongside delivery. Collaborate closely with H2O.ai product and engineering teams to surface customer feedback, shape roadmap input, and resolve platform-level issues. What We Are Looking For Experience & Background 8+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. Demonstrable experience leading technical delivery across complex, multi-stakeholder enterprise engagements - not just executing within them. Demonstrable experience building LLM-powered applications - RAG pipelines, agentic workflows, fine-tuned models, or similar. Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (LangChain, LlamaIndex, or equivalent). Experience deploying AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes). Skills & Capabilities Proven ability to manage multiple concurrent workstreams and coordinate cross-functional teams toward shared delivery milestones. Deep understanding of modern GenAI concepts: prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. Solid grounding in classical ML - able to select the right tool for the problem, not just default to the latest LLM. Backend development skills: REST APIs, containerisation (Docker/Kubernetes), and CI/CD pipelines for AI applications. Strong executive communication - able to run a board-level briefing one hour and a technical design review the next, credibly. Comfortable with ambiguity and able to set direction for a team when requirements are incomplete or evolving. How to Stand Out From the Crowd Kaggle or competitive ML experience. Familiarity with H2O.ai products, Wave, or H2O Document AI. Experience in financial services, healthcare, or other regulated industry AI deployments. Exposure to tabular foundation models, AutoML, or enterprise ML platforms. Prior experience in a customer-facing or field engineering role. Why H2O.ai? Market leader in total rewards Remote-friendly culture Flexible working environment Be part of a world-class team Career growth H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis. H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We've made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. H2O.ai employs the world's top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company's purpose. Please visit

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.

Senior. Distinguished AI Engineer - Agentic AI 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 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. You will contribute to the north star platform architecture, continuously publishing and refining living diagrams and canonical APIs that cover agent orchestration, RAG pipelines, prompt libraries and multi-tenant policy enforcement. A major emphasis is around standardizing and automating agentic workflows : you will evaluate agentic frameworks such LangGraph, AutoGen, Semantic Kernal, CrewAI and LlamaIndex and then harden / blend patterns that best meet enterprise SLAs do that 90% of new apps adopt them. Developer experience is another cornerstone. You will contribute to crafting an end to end GenAI SDK, CLI and starter kits that let AI engineers spin up secure, observable agentic workflows in under minutes, shrinking prototyping to production timelines by 30%. Trust and safety remain paramount; you will help bring together a vision of central guardrail services - prompt firewalls, content-filter hooks, red team harnesses and audit APIs - consumed by every application to ensure zero Sev4 incidents. You will collaborate with cross organization architects to drive end to end performance by optimizing orchestration - level batching, retrieval caching, heuristic tuning to achieve reductions in per token spend. You will accelerate innovation by incubating proof of concepts and driving RFCs such as hierarchical agent memory, multimodal guardrails, multimodal RAG. You'll own central Helm charts, operators and CRDs that auto scale agents to hit tenant SLAs Finally you will coach and evangelize - hosting architecture office hours, mentoring Staff, Principal and Senior engineers, authoring technical design documents and blogs and representing Capital One at Tier1 AI conferences - to amplify platform vision across internal and external communities. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or AI plus at least 10 years of experience developing AI and ML algorithms or technologies, or Master's degree 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) 2+ years of experience supporting Agentic Frameworks (LangChain, CrewAI, Semantic Kernel (Microsoft), or AutoGen) 2+ years of experience with LLMOps (Google Cloud Vertex AI, Amazon SageMaker, Azure Machine Learning) 8+ years of experience designing mission-critical machine learning platforms 2+ years of 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 Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading GenAI or LLM-Powered application architectures in production Deep understanding of Responsible AI, data privacy and multi-tenant security patterns K8s mastery (multi-region clusters, service mesh) Experience staying abreast of the latest AI research and AI systems and applying novel techniques in production Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Distinguished AI Engineer 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 . click apply for full job details

RZR Global, Inc. (San Francisco, CA) seeks a Senior Data Scientist. Design and implement machine learning models and scalable data pipelines; develop predictive algorithms; conduct statistical analysis; deploy models in distributed/containerized environments. Req'd: Bachelor's degree in Electronics, Computer Science, Data Science, Computer Engineering, or related technical field plus 30 months experience in data science, machine learning, or related field. Must have experience with Python, SQL, ML frameworks, Hadoop/Spark, Docker/Kubernetes, REST APIs, statistical modeling, data visualization tools, and AWS or Azure. Salary $164,403.00 per year. Send resume to (email removed)

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.

Senior. Distinguished AI Engineer - Agentic AI 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 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. You will contribute to the north star platform architecture, continuously publishing and refining living diagrams and canonical APIs that cover agent orchestration, RAG pipelines, prompt libraries and multi-tenant policy enforcement. A major emphasis is around standardizing and automating agentic workflows : you will evaluate agentic frameworks such LangGraph, AutoGen, Semantic Kernal, CrewAI and LlamaIndex and then harden / blend patterns that best meet enterprise SLAs do that 90% of new apps adopt them. Developer experience is another cornerstone. You will contribute to crafting an end to end GenAI SDK, CLI and starter kits that let AI engineers spin up secure, observable agentic workflows in under minutes, shrinking prototyping to production timelines by 30%. Trust and safety remain paramount; you will help bring together a vision of central guardrail services - prompt firewalls, content-filter hooks, red team harnesses and audit APIs - consumed by every application to ensure zero Sev4 incidents. You will collaborate with cross organization architects to drive end to end performance by optimizing orchestration - level batching, retrieval caching, heuristic tuning to achieve reductions in per token spend. You will accelerate innovation by incubating proof of concepts and driving RFCs such as hierarchical agent memory, multimodal guardrails, multimodal RAG. You'll own central Helm charts, operators and CRDs that auto scale agents to hit tenant SLAs Finally you will coach and evangelize - hosting architecture office hours, mentoring Staff, Principal and Senior engineers, authoring technical design documents and blogs and representing Capital One at Tier1 AI conferences - to amplify platform vision across internal and external communities. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or AI plus at least 10 years of experience developing AI and ML algorithms or technologies, or Master's degree 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) 2+ years of experience supporting Agentic Frameworks (LangChain, CrewAI, Semantic Kernel (Microsoft), or AutoGen) 2+ years of experience with LLMOps (Google Cloud Vertex AI, Amazon SageMaker, Azure Machine Learning) 8+ years of experience designing mission-critical machine learning platforms 2+ years of 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 Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading GenAI or LLM-Powered application architectures in production Deep understanding of Responsible AI, data privacy and multi-tenant security patterns K8s mastery (multi-region clusters, service mesh) Experience staying abreast of the latest AI research and AI systems and applying novel techniques in production Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Distinguished AI Engineer 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 . click apply for full job details

Distinguished AI Engineer - Agentic AI 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 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. Why this Role Matters: We are building an enterprise Generative AI Platform that lets dozens of product teams compose powerful, safe and explainable AI capabilities - without wrestling with model minutiae or infra plumbing. You will design the agentic workflow framework, shared services such as memory, guardrails, vector search, SDKs and blueprints that translate foundation model power into production grade applications used by millions of users across multiple lines of businesses. 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. You will contribute to the north star platform architecture, continuously publishing and refining living diagrams and canonical APIs that cover agent orchestration, RAG pipelines, prompt libraries and multi-tenant policy enforcement. A major emphasis is around standardizing and automating agentic workflows : you will evaluate agentic frameworks such LangGraph, AutoGen, Semantic Kernal, CrewAI and LlamaIndex and then harden / blend patterns that best meet enterprise SLAs do that 90% of new apps adopt them. Developer experience is another cornerstone. You will contribute to crafting an end to end GenAI SDK, CLI and starter kits that let AI engineers spin up secure, observable agentic workflows in under minutes, shrinking prototyping to production timelines by 30%. Trust and safety remain paramount; you will help bring together a vision of central guardrail services - prompt firewalls, content-filter hooks, red team harnesses and audit APIs - consumed by every application to ensure zero Sev4 incidents. You will collaborate with cross organization architects to drive end to end performance by optimizing orchestration - level batching, retrieval caching, heuristic tuning to achieve reductions in per token spend. You will accelerate innovation by incubating proof of concepts and driving RFCs such as hierarchical agent memory, multimodal guardrails, multimodal RAG. You'll own central Helm charts, operators and CRDs that auto scale agents to hit tenant SLAs Finally you will coach and evangelize - hosting architecture office hours, mentoring Staff, Principal and Senior engineers, authoring technical design documents and blogs and representing Capital One at Tier1 AI conferences - to amplify platform vision across internal and external communities. 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) 2+ years of experience supporting Agentic Frameworks (LangChain, CrewAI, Semantic Kernel (Microsoft), or AutoGen) 2+ years of experience with LLMOps (Google Cloud Vertex AI, Amazon SageMaker, Azure Machine Learning) 8+ years of experience designing mission-critical machine learning platforms 2+ years of 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 Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience leading GenAI or LLM-Powered application architectures in production Deep understanding of Responsible AI, data privacy and multi-tenant security patterns Experience as a Staff-plus or Distinguished IC engineer influencing 50+ engineers and C-suite stakeholders K8s mastery (multi-region clusters, sericie mesh) Experience staying abreast of the latest AI research and AI systems and applying novel techniques in production 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. . click apply for full job details

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.

GXM Technologies LLC seeks a Senior Digital Engineer specializing in MBSE and Data Science to support mission-critical defense and intelligence programs. In this role, you will architect and maintain SysML-based models, integrate geospatial, C4ISR, AI/ML, and cyber capabilities, and build advanced analytics to inform complex system decisions. You will collaborate with cross-functional teams, drive digital engineering best practices, mentor junior staff, and contribute to R&D efforts, delivering secure, scalable solutions that directly support U.S. national security objectives. Responsibilities Lead development of MBSE models to support complex defense and intelligence systems Design and implement data science and analytics solutions for mission-focused applications Integrate geospatial, C4 ISR, AI/ML, and cyber capabilities into digital engineering workflows Collaborate with cross-functional teams to define system architecture and requirements Develop prototypes and tools to support advanced R&D and systems integration Ensure model traceability, verification, and validation across the system lifecycle Optimize data pipelines, feature engineering, and model performance for production use Document designs, analyses, and technical decisions for stakeholders and customers Mentor junior engineers and data scientists in MBSE and analytics best practices Support proposal efforts and technical presentations to government clients Required Skills Model-Based Systems Engineering (MBSE) Sys ML or similar modeling languages Systems architecture and requirements engineering Data science and statistical analysis Python or similar programming languages Machine learning frameworks (e.g., Tensor Flow, Py Torch, scikit-learn) Geospatial data and tools (e.g., GIS, geospatial libraries) C4 ISR or defense/intelligence systems domain knowledge Data pipeline and ETL development Cloud or containerized environments for analytics