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Annapurna Labs designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago-even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world. The Machine Learning Server Software Team is looking for candidates interested in writing data-driven software for our Machine Learning servers. We build production software to initialize and monitor the most advanced machine learning acceleration servers in the world. We touch technologies including accelerator chip initialization, setting up clocks and voltages, to systems level device drivers for I2C infrastructure pervasive in the server and everything in between. Our team does not work on machine learning algorithms, but rather on the physical systems (hardware) which execute and accelerate those machine learning algorithms. Data paths, PCIe, SPI, I2C, accelerator inner-workings are our bread and butter. Come join our team. Key job responsibilities - Member of a team responsible for the software associated with server components and integration in to EC2. - Working with the MLA Hardware, Test and Manufacturing teams to create a coordinated software package to enable both qualification as well as rapid deployment of software. - Developing software (C, C++, Python, Lua) which can be maintained, improved upon, documented, tested, and reused. A day in the life The MLA Systems Software team was formed to focus on server software primarily for initialization, monitoring, debug, testing, qualification, and manufacturing. At a high-level our goal is to find ways to help the organization scale though the use of software and automation. About the team Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. About AWS Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. Mentorship & Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. BASIC QUALIFICATIONS - 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience programming with at least one software programming language PREFERRED QUALIFICATIONS - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Bachelor's degree in computer science or equivalent Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company's reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at . USA, CA, Cupertino - 165 600.00 USD annually USA, TX, Austin - 143 400.00 USD annually

The Last Resort That Actually Works: When Every Other Path Did not You Have Already Tried the Usual Advice You rewrote the resume. You networked. You applied daily. You took a cheaper bootcamp. You used a staffing firm. You practiced on LeetCode at midnight. You still are not hired-or you get interviews and lose them. for the jobseeker who is out of tactics: recent graduates, people who cannot get interviews, people who fail interviews, caregivers back from family leave, career-gap candidates, outdated-stack professionals, laid-off reentrants, OPT students, career switchers, and bootcamp grads still unemployed. Several Hireable Paths JOPP targets software engineer, Data Analyst/Scientist and Java developer roles with Spring, microservices, DevOps, and DSA. Data Science JOPP targets data analyst, data scientist, data engineer, and AI/ML roles with Python, SQL, BI, cloud data platforms, ML, and GenAI. genuine projects, a 5,000+ interview-question database, and outreach across 24,000+ tech-client contacts. Since 2010, we've helped thousands of candidates land full-time jobs at tech leaders like Google, Apple, PayPal, Visa, Western Union, Wells Fargo, Client, Paypal, Banking, Wayfair, Client, Client and hundreds more with Job offers of $95k to $154k. Synergisticit focuses on closing the gap between your tech skills and what employers want now. You're not alone-and you're not the problem. The reality? Most CS grads struggle to land interviews because their resumes look just like everyone else's. Employers want more than a diploma-they want proven, practical skills, real-world tools, and candidates who are ready to perform from day one. That's exactly what SynergisticIT delivers. Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/Data Engineers/ Data Scientists, Machine Learning engineers for full time positions with clients. We Focus on Java /Full stack/Devops and Data Science /Data Engineers/Data analysts/BI Analysts/ Machine learning/AI candidates Ideal Candidates: Recent grads in CS, Engineering, Math, or Statistics with limited or no job experience Jobseekers who had layoffs due to Downsizing and want to get in demand tech stack Professionals seeking a career switch to tech Candidates with career gaps or lacking real-world experience Individuals looking to boost their skill portfolio for better job prospects Computer Science grads with limited or no job experience Students who recently finished their Bachelor's or Master's programs Those struggling to land interviews despite having experience Please check below links: Event videos (OCW, JavaOne, Gartner): USA Today feature Explore JOPP: Reviews: SynergisticIT Reviews & Video Testimonials please read our blogs Why do Tech Companies not Hire recent Computer Science Graduates Technical Skills or Experience? Which one is important to get a Job? When Nothing Else Works, JOPP Works That line is the point JOPP is not magic, and it is not passive: attendance, assessments, relocation openness where required, interview show-up, and project completion matter. It is a full system for people who discovered that certificates, job boards, and "placement support" do not get them hired. If every other path stalled, stop collecting tactics. When nothing else works, JOPP works. Please note: Resume databases are shared with clients and interested clients will reach out directly if they find a qualified candidate for their req. Resume submissions may be shared with our JOPP team database also. Please unsubscribe if contacted or if you don't want to be contacted please don't submit your resume.

At Credit Acceptance, we are building on the foundation of a successful business while investing in the future through technology, data, AI, and continuous improvement. As we continue to evolve, our Team Members play an active role in improving experiences, driving meaningful change, and shaping the future of our business. We foster an environment where people are empowered to contribute ideas, develop their careers, make an impact, and help lead our continued transformation. Our Engineering teams are helping shape the future of Credit Acceptance through innovation. Team Members collaborate across the organization to solve complex challenges, build impactful solutions, challenge the status quo, and support informed business decisions. We value curiosity, continuous learning, and new ideas from people who are passionate about driving modernization and meaningful business impact. Outcomes and Activities: Own the deployment path for ML and GenAI models end to end training and inference pipelines, model registry and versioning, serving endpoints, and controlled promotion across development, QA and production. Own runtime health for models in production: monitoring, alerting, drift and quality-regression detection, latency and throughput objectives, capacity and autoscaling behavior, and incident response through to root cause and a closed corrective action. Operate the agent runtime layer. Route production agents through the enterprise AI Gateway and MCP Gateway rather than direct model and tool access, migrate existing agents onto that governed path, and keep tool surfaces scoped, versioned and least-privilege as they change. Own evaluation of agents in production, not just before release. Online scoring and behavioral monitoring, quality-regression and drift detection against pinned baselines, sampling and judge pipelines, and the release-gate mechanics that stop a regression from shipping. Build and maintain the observability and evaluation substrate other teams depend on: trace and telemetry capture including multi-turn and multi-step agent traces, logging standards, evaluation pipeline plumbing, and the data contracts underneath them. Own platform unit economics. Measure and manage cost per inference, per document and per interaction, and produce the platform and infrastructure cost analysis that informs build-versus-buy and hosting decisions. Make the paved road real. Deliver reusable pipeline templates, deployment patterns, reference implementations and internal tooling so product teams adopt the standard path because it is faster, not because it is mandated. Partner with Cloud Engineering, Data Engineering, Security and SRE so the ML platform sits inside enterprise governance, identity and observability rather than beside it. Respond to AI-specific production incidents and drive them to a closed corrective action: prompt injection attempts, rogue-agent cost spikes, data-classification exposure through a tool call, delegation abuse between agents, and model endpoint failures. Maintain the architecture documentation and system diagrams for the ML platform and keep them accurate enough to be used in design review. Mentor engineers and interns on production ML practice and raise the operating standard through design and code review rather than through rework. Competencies: The following items detail how you will be successful in this role. Customer Empathy: Customer Empathy is the ability to understand the perspectives, pain points, and experiences of customers. It involves actively putting oneself in the customer's shoes, comprehending their needs and challenges, and using that understanding to provide a better, more customer-centric experience. Engineering Excellence: Engineering Excellence is about bringing great craftsmanship and thought leadership to deliver an outstanding product that delights customers and solves for the business. This involves the pursuit and achievement of high standards, best practices, innovation, and superior solutions. One Team: A One Team mindset refers to a collaborative approach across the organization, where individuals work together seamlessly, without boundaries, as a single, cohesive team. Shared goals, open communication and mutual support create a sense of collective purpose. This enables teams to navigate challenges and pursue shared objectives more effectively. Owner's Mindset: Owner's Mindset involves adopting a set of behaviors that reflect a sense of responsibility, accountability, strategic thinking, and a proactive approach to managing your domain. As an owner, you understand the business and your domain(s) deeply and solve for the right outcome for the domain(s) and the business. Requirements Bachelor's degree in Computer Science, Engineering, Statistics or a relevant technical field with at least 7 years of relevant experience, or a Master's degree in one of those fields with at least 5 years of relevant experience. 5+ years building and operating production ML or AI systems, with direct ownership of at least two of: training or inference pipelines, model serving infrastructure, model registry and versioning, or production monitoring and alerting. Demonstrated ownership of a production ML or AI service through its full operating life: deployed it, monitored it, was paged for it, diagnosed a failure, and shipped the fix. Strong Python and SQL, with production-quality engineering practice: version control, testing, code review, and CI/CD applied to ML workloads rather than only to application code. Hands-on experience with a cloud ML platform in production. AWS and Databricks strongly preferred, including model serving, job orchestration, and a model registry or experiment tracking system such as MLflow. Working knowledge of how LLM and GenAI workloads differ operationally from traditional ML: token cost and latency behavior, caching and batching, non-deterministic output. Experience running LLM or agent applications behind a gateway or proxy layer, and able to build best practices for model routing and fallback, credential and key management, rate limiting and budget enforcement. Working knowledge of tool-calling architecture for agents, including the Model Context Protocol: what an MCP server is, how tools are scoped and authorized, and why tool access is brokered through a gateway rather than granted directly. Experience with containerization and infrastructure as code. Ability to communicate technical and non-technical trade-offs clearly in writing to an audience that includes both engineers and non-engineers. Candidates must reside in or be willing to relocate to one of the following hub locations: the greater Southfield, Michigan, area; the greater Bellevue, Washington, area; or the San Francisco Bay Area, California. Preferred Production experience with GPU-backed model serving, including autoscaling behavior under concurrent load, cold-start management and cost control. Experience with OpenTelemetry and an enterprise observability platform such as Dynatrace, including instrumenting AI workloads rather than only conventional services. Experience with model serving efficiency techniques: quantization, parameter-efficient fine-tuning, distillation or inference optimization. Experience with data governance and access control on a lakehouse platform, such as Databricks Unity Catalog. Experience operating AI systems in a regulated industry, particularly financial services, including auditability, retention and access-control requirements. Experience with agentic or multi-step AI systems in production, including tracing and debugging multi-turn behavior. Hands-on experience with a managed agent or tool gateway, such as AWS Bedrock AgentCore Gateway, and with running MCP servers in a governed environment. Familiarity with emerging agent interoperability and agent identity standards, including Agent2Agent (A2A) style agent-to-agent delegation, agent discovery and capability advertisement, and workload identity for non-human actors. Knowledge and Skills Ability to communicate complex technical information, both verbal and written, to all levels, including senior leadership. Ability to solve problems at the source by offering simple, working solutions. Responds promptly and effectively to resolve incidents, tasks, and projects. Demonstrated ability and motivation to teach others. Ability to gain the trust of others and build solid relationships across and vertically throughout the organization. Effectively prioritize and execute tasks in a high-pressure environment. Target Compensation: This position offers a competitive base salary, with a range of $184,943- $258,920. This position is eligible for an annual variable incentive of cash and equity, between 10- 20% of base salary. Actual amounts are based on individual performance. Final compensation within the range is influenced by many factors including assigned hub location, role-specific skills, depth and experience level, industry background, relevant education and certifications. This position follows a hybrid work model, offering two work-from-home days and three standard in-office days each week with the team and key stakeholders at the local office. INDENGLP Benefits Excellent benefits package that includes 401(K) match, adoption assistance, parental leave, tuition reimbursement, comprehensive medical/ dental/vision and many nonstandard benefits that make us a Great Place to Work Our Company Values: To be successful in this role, Team Members need to be: Positive by maintaining resiliency and focusing on solutions Respectful by collaborating and actively listening Insightful by cultivating innovation, accumulating business and role specific knowledge, demonstrating self-awareness and making quality decisions Direct by effectively communicating and conveying courage Earnest by taking accountability . click apply for full job details

Job Description Job Description Manager, AI & Research Computing Initiatives Job ID: 3743 Client: Boston University Location: Boston, MA Duration: 9-Month Contract Work Arrangement: Hybrid - Must be local to Boston, MA Schedule: 40 Hours per Week Industry: Higher Education / Artificial Intelligence / Research Computing Job Overview Sigma Inc. is seeking an experienced Manager, AI & Research Computing Initiatives for a 9-month contract opportunity supporting Boston University in Boston, MA. This leadership position will drive the strategy, planning, and development of artificial intelligence infrastructure and research computing initiatives. The ideal candidate will have a strong background in AI/ML infrastructure, High-Performance Computing (HPC), GPU computing, cloud infrastructure, MLOps, and technical team management . The Manager will lead the technical roadmap for AI-enabled research computing, anticipate emerging infrastructure requirements, and collaborate with faculty, researchers, academic departments, and IT leadership to develop scalable solutions supporting AI-intensive research projects. This role combines technical strategy, AI infrastructure planning, research computing operations, project coordination, and people management. The successful candidate will serve as a technical leader and subject matter expert, helping advance AI and machine learning capabilities across the university's research environment. Candidates must be local to the Boston, MA area and available to work in a hybrid arrangement. Key ResponsibilitiesAI Research Computing Strategy & Infrastructure Develop and drive the technical roadmap for AI-enabled research computing and infrastructure. Lead planning and capacity management for GPU computing, accelerators, and high-performance computing resources. Evaluate and recommend AI/ML infrastructure, containerized computing environments, and MLOps tools. Anticipate emerging requirements related to AI workloads, data pipelines, model training, and model-serving infrastructure. Provide technical guidance and expertise on AI infrastructure, research computing, and emerging AI technologies. Collaborate with research computing leadership to develop AI/ML strategies and infrastructure plans. Research emerging technologies, industry standards, and best practices in artificial intelligence and automation. Project & Service Coordination Coordinate daily research computing projects, service requests, and incident management activities. Monitor service delivery, identify potential delays, and escalate critical issues to leadership. Coordinate cross-functional activities between research computing teams, IT infrastructure groups, and academic research departments. Ensure researchers receive appropriate technical resources and infrastructure support. Provide operational updates and reports to Research Computing leadership. Team Leadership & Management Supervise, mentor, and develop research computing team members. Establish priorities, assign workloads, and oversee daily service delivery. Support employee performance management, professional development, hiring, and onboarding. Promote collaboration, accountability, and continuous improvement across the team. Operational Reporting & Business Process Analysis Develop annual, monthly, and ad hoc reports on computing resources, system utilization, storage services, and infrastructure capacity. Analyze operational metrics to support purchasing decisions, resource allocation, and strategic planning. Evaluate and improve research project workflows and service delivery processes. Support research computing projects involving secure research environments and regulated data systems. Collaborate on chargeback models, resource utilization, and service management processes. Training & Documentation Coordinate technical training programs for academic researchers, faculty, staff, and technical teams. Manage synchronous and asynchronous training initiatives. Coordinate the development of video tutorials, technical guides, and educational materials. Maintain and update research computing documentation, knowledge bases, and technical resources. Promote knowledge sharing and effective use of research computing services. Required Qualifications Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, or a related technical field, or equivalent professional experience. Demonstrated experience managing AI/ML infrastructure, research computing, high-performance computing, or related technical environments. Strong understanding of AI/ML infrastructure requirements, GPU computing, accelerators, and high-performance computing resources. Experience with containerized computing environments and AI/ML workflows. Knowledge of MLOps tools, machine learning infrastructure, and model deployment environments. Experience leading technical projects and coordinating cross-functional teams. Previous experience supervising, mentoring, or managing technical professionals. Strong understanding of IT infrastructure, compute resources, storage systems, and research technology environments. Experience with operational reporting, resource utilization, and business process analysis. Excellent communication and stakeholder management skills. Ability to work with faculty, researchers, academic departments, and technical leadership. Strong organizational, analytical, and problem-solving skills. Preferred Qualifications Experience working in a university, academic research, or scientific computing environment. Experience managing High-Performance Computing (HPC) environments. Hands-on knowledge of GPU clusters, NVIDIA GPUs, accelerators, and AI compute infrastructure. Experience with Kubernetes, Docker, containers, and orchestration technologies. Familiarity with MLOps platforms, machine learning pipelines, and AI model-serving infrastructure. Experience supporting AI-intensive research projects and grant-funded research initiatives. Knowledge of secure research environments, regulated research systems, and research data governance. Experience developing technical roadmaps, infrastructure strategies, and capacity planning initiatives. Experience managing research computing services and technical support teams. Technical Skills & Search Keywords AI Infrastructure AI/ML Infrastructure Artificial Intelligence Machine Learning Research Computing High-Performance Computing (HPC) GPU Computing NVIDIA GPUs GPU Clusters Accelerated Computing MLOps Kubernetes Docker Containerization Model Deployment Model Serving AI Workflows Cloud Infrastructure Data Pipelines Research Data Infrastructure Infrastructure Planning Capacity Planning Technical Roadmap HPC Management Research IT IT Operations Team Leadership Project Management Resource Utilization Secure Research Environments Ideal Candidate Job Titles Manager, AI Infrastructure AI Infrastructure Manager Research Computing Manager High-Performance Computing (HPC) Manager HPC Infrastructure Manager AI/ML Platform Manager Machine Learning Infrastructure Manager Research IT Manager Director of Research Computing AI Engineering Manager Technical Infrastructure Manager Research Computing Technical Lead Scientific Computing Manager Work Arrangement & Schedule Hybrid work arrangement. Must be local to Boston, MA. 40 hours per week. 9-month contract. Collaboration with university researchers, faculty, and IT leadership. Contract Details Job Title: Manager, AI & Research Computing Initiatives Job ID: 3743 Client: Boston University Location: Boston, MA Duration: 9 Months Work Arrangement: Hybrid - Local Boston candidates only Schedule: 40 Hours per Week

Job Description Job Description Manager, AI & Research Computing Initiatives Job ID: 3743 Client: Boston University Location: Boston, MA Duration: 9-Month Contract Work Arrangement: Hybrid - Must be local to Boston, MA Schedule: 40 Hours per Week Industry: Higher Education / Artificial Intelligence / Research Computing Job Overview Sigma Inc. is seeking an experienced Manager, AI & Research Computing Initiatives for a 9-month contract opportunity supporting Boston University in Boston, MA. This leadership position will drive the strategy, planning, and development of artificial intelligence infrastructure and research computing initiatives. The ideal candidate will have a strong background in AI/ML infrastructure, High-Performance Computing (HPC), GPU computing, cloud infrastructure, MLOps, and technical team management . The Manager will lead the technical roadmap for AI-enabled research computing, anticipate emerging infrastructure requirements, and collaborate with faculty, researchers, academic departments, and IT leadership to develop scalable solutions supporting AI-intensive research projects. This role combines technical strategy, AI infrastructure planning, research computing operations, project coordination, and people management. The successful candidate will serve as a technical leader and subject matter expert, helping advance AI and machine learning capabilities across the university's research environment. Candidates must be local to the Boston, MA area and available to work in a hybrid arrangement. Key Responsibilities AI Research Computing Strategy & Infrastructure Develop and drive the technical roadmap for AI-enabled research computing and infrastructure. Lead planning and capacity management for GPU computing, accelerators, and high-performance computing resources. Evaluate and recommend AI/ML infrastructure, containerized computing environments, and MLOps tools. Anticipate emerging requirements related to AI workloads, data pipelines, model training, and model-serving infrastructure. Provide technical guidance and expertise on AI infrastructure, research computing, and emerging AI technologies. Collaborate with research computing leadership to develop AI/ML strategies and infrastructure plans. Research emerging technologies, industry standards, and best practices in artificial intelligence and automation. Project & Service Coordination Coordinate daily research computing projects, service requests, and incident management activities. Monitor service delivery, identify potential delays, and escalate critical issues to leadership. Coordinate cross-functional activities between research computing teams, IT infrastructure groups, and academic research departments. Ensure researchers receive appropriate technical resources and infrastructure support. Provide operational updates and reports to Research Computing leadership. Team Leadership & Management Supervise, mentor, and develop research computing team members. Establish priorities, assign workloads, and oversee daily service delivery. Support employee performance management, professional development, hiring, and onboarding. Promote collaboration, accountability, and continuous improvement across the team. Operational Reporting & Business Process Analysis Develop annual, monthly, and ad hoc reports on computing resources, system utilization, storage services, and infrastructure capacity. Analyze operational metrics to support purchasing decisions, resource allocation, and strategic planning. Evaluate and improve research project workflows and service delivery processes. Support research computing projects involving secure research environments and regulated data systems. Collaborate on chargeback models, resource utilization, and service management processes. Training & Documentation Coordinate technical training programs for academic researchers, faculty, staff, and technical teams. Manage synchronous and asynchronous training initiatives. Coordinate the development of video tutorials, technical guides, and educational materials. Maintain and update research computing documentation, knowledge bases, and technical resources. Promote knowledge sharing and effective use of research computing services. Required Qualifications Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, or a related technical field, or equivalent professional experience. Demonstrated experience managing AI/ML infrastructure, research computing, high-performance computing, or related technical environments. Strong understanding of AI/ML infrastructure requirements, GPU computing, accelerators, and high-performance computing resources. Experience with containerized computing environments and AI/ML workflows. Knowledge of MLOps tools, machine learning infrastructure, and model deployment environments. Experience leading technical projects and coordinating cross-functional teams. Previous experience supervising, mentoring, or managing technical professionals. Strong understanding of IT infrastructure, compute resources, storage systems, and research technology environments. Experience with operational reporting, resource utilization, and business process analysis. Excellent communication and stakeholder management skills. Ability to work with faculty, researchers, academic departments, and technical leadership. Strong organizational, analytical, and problem-solving skills. Preferred Qualifications Experience working in a university, academic research, or scientific computing environment. Experience managing High-Performance Computing (HPC) environments. Hands-on knowledge of GPU clusters, NVIDIA GPUs, accelerators, and AI compute infrastructure. Experience with Kubernetes, Docker, containers, and orchestration technologies. Familiarity with MLOps platforms, machine learning pipelines, and AI model-serving infrastructure. Experience supporting AI-intensive research projects and grant-funded research initiatives. Knowledge of secure research environments, regulated research systems, and research data governance. Experience developing technical roadmaps, infrastructure strategies, and capacity planning initiatives. Experience managing research computing services and technical support teams. Technical Skills & Search Keywords AI Infrastructure AI/ML Infrastructure Artificial Intelligence Machine Learning Research Computing High-Performance Computing (HPC) GPU Computing NVIDIA GPUs GPU Clusters Accelerated Computing MLOps Kubernetes Docker Containerization Model Deployment Model Serving AI Workflows Cloud Infrastructure Data Pipelines Research Data Infrastructure Infrastructure Planning Capacity Planning Technical Roadmap HPC Management Research IT IT Operations Team Leadership Project Management Resource Utilization Secure Research Environments Ideal Candidate Job Titles Manager, AI Infrastructure AI Infrastructure Manager Research Computing Manager High-Performance Computing (HPC) Manager HPC Infrastructure Manager AI/ML Platform Manager Machine Learning Infrastructure Manager Research IT Manager Director of Research Computing AI Engineering Manager Technical Infrastructure Manager Research Computing Technical Lead Scientific Computing Manager Work Arrangement & Schedule Hybrid work arrangement. Must be local to Boston, MA. 40 hours per week. 9-month contract. Collaboration with university researchers, faculty, and IT leadership. Contract Details Job Title: Manager, AI & Research Computing Initiatives Job ID: 3743 Client: Boston University Location: Boston, MA Duration: 9 Months Work Arrangement: Hybrid - Local Boston candidates only Schedule: 40 Hours per Week

Job Description Job Description DBA/Engineer Job Number: 26-01876 Use your skills where innovative technology solutions begin. ECLARO is looking for a DBA/Engineer for our client in Norfork, VA. ECLARO's client is a leading technology solutions provider, collaborating with customers to manage their needs and achieve success in their business goals. If you're up to the challenge, then take a chance at this rewarding opportunity! Responsibilities: Install, configure, maintain, patch, upgrade, secure, and support Oracle Database, Oracle APEX, ORDS, and related application environments. Monitor database health, availability, performance, storage utilization, capacity planning, and operational metrics across all environments. Design, develop, maintain, troubleshoot, and optimize Oracle APEX applications and supporting PL/SQL components. Perform database performance analysis and tuning utilizing AWR reports, ASH reports, SQL Trace, Explain Plans, OEM, and other Oracle diagnostic tools. Investigate and resolve database performance issues involving SQL execution, indexing, partitioning, concurrency, locking, blocking, deadlocks, memory management, and resource utilization. Manage database backup and recovery processes, disaster recovery planning, database cloning, environment refreshes, migrations, upgrades, and patching activities. Administer database security, including users, roles, privileges, encryption, auditing, access controls, and compliance with security best practices. Develop automation solutions using Shell Scripting, SQL Plus, SQLcl, PL/SQL, and related tools to improve operational efficiency. Maintain system documentation, architectural diagrams, operational procedures, recovery plans, runbooks, and technical standards. Support production incidents, conduct root cause analysis (RCA), implement corrective actions, and participate in continuous improvement efforts. Collaborate with developers, system administrators, network engineers, security personnel, and business stakeholders to support Oracle-based applications and services. Provide technical guidance, mentoring, and operational support to developers, engineers, technical staff, and college personnel utilizing Oracle database and APEX solutions. Plan, coordinate, and participate in planned maintenance activities and provide on-call support for critical database and application issues as needed. Required Qualifications: 7+ years of hands-on experience administering Oracle Database environments in enterprise production settings. 5+ years of demonstrated experience developing, deploying, supporting, and maintaining Oracle Apex applications. Extensive expertise with Oracle PL/SQL development, including packages, procedures, functions, triggers, views, collections, dynamic SQL, and performance optimization. Strong experience administering Oracle Linux and/or Red Hat Enterprise Linux servers supporting Oracle databases and Oracle application environments. Experience managing Oracle APEX environments, Oracle REST Data Services (ORDS), Apache/Tomcat web services, and related Oracle application infrastructure. Demonstrated experience with Oracle BI Publisher installation, configuration, maintenance, troubleshooting, and report development. Thorough understanding of Software Development Lifecycle (SDLC) methodologies, source control, deployment processes, testing, release management, and change control practices. Experience implementing, maintaining, and supporting Development, QA, UAT, and Production environments. Preferred Qualifications: Oracle Database Administration (DBA) certifications. Oracle APEX certifications or advanced APEX development experience. Experience with Oracle Data Pump, RMAN, Data Guard, Oracle Enterprise Manager (OEM), and Oracle REST Data Services (ORDS). Experience integrating Oracle applications with Active Directory, Entra ID, SAML, REST APIs, web services, and third-party enterprise systems. Experience leveraging generative AI, machine learning, and AI-assisted productivity tools (e.g., Microsoft Copilot, ChatGPT, GitHub Copilot, Claude Code, Codex, and similar platforms) to improve operational efficiency, accelerate development, enhance troubleshooting, automate workflows, and support innovative technical solutions and business use cases. Experience working within higher education, government, healthcare, or similarly regulated enterprise environments. If hired, you will enjoy the following ECLARO Benefits: 401k Retirement Savings Plan administered by Merrill Lynch Commuter Check Pretax Commuter Benefits Eligibility to purchase Medical, Dental & Vision Insurance through ECLARO If interested, you may contact: Homer Ballega Homer Ballega LinkedIn Equal Opportunity Employer: ECLARO values diversity and does not discriminate based on Race, Color, Religion, Sex, Sexual Orientation, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status, in compliance with all applicable laws.

Job Description Job Description Description: Columbia Technology Partners is seeking an AI/ML Engineer to support mission-critical intelligence operations within a fast-paced national security environment. In this role, you will work directly with mission users to capture complex analytical workflows, identify operational decision points, and develop AI-enabled solutions that improve efficiency, accessibility, and decision-making. The ideal candidate will have experience designing and implementing AI-driven workflows, integrating large language models (LLMs) into operational processes, and developing solutions that operate effectively within secure enterprise environments. You will collaborate closely with analysts, operators, developers, and mission leadership to deliver scalable capabilities that align with mission requirements and security expectations. Key Responsibilities: Capture and document user workflows, translating operational needs into automation requirements and executable solutions. Design, develop, and implement AI/ML capabilities including LLM-powered workflows, agentic automation, and hybrid AI solutions. Integrate AI systems with APIs, enterprise data sources, and mission platforms. Develop and maintain Python-based applications and automation tools. Collaborate with technical and mission stakeholders to ensure reliable deployment and operational effectiveness. Ensure solutions comply with security, governance, and performance requirements within classified environments. Qualifications: Bachelor's degree and 14+ years of experience, including 3+ years supporting AI/ML, data science, or software engineering initiatives within cyber, intelligence, or national security environments. Experience capturing operational workflows and translating requirements into automation, process maps, or executable solutions. Experience designing and implementing LLM-powered or agentic workflows, including orchestration and tool integration. Experience integrating AI capabilities with APIs, enterprise data sources, and mission platforms. Strong Python development skills and experience building production-ready applications or automation solutions. Desired Skills: Experience engineering and deploying AI capabilities within on-premises, air-gapped, or multi-classification environments. Experience with AWS and/or Azure, particularly in restricted or mission-focused environments. Experience with AI development frameworks such as LangChain, LangGraph, PydanticAI, or CrewAI. Experience with machine learning frameworks including PyTorch, TensorFlow, vLLM, or llama.cpp. Familiarity with cyber intelligence workflows, operational analytics, and mission-focused data environments; a Master's degree in a related technical field is a plus. Requirements: U.S. Citizenship is required for all applicants. CTP is an equal opportunity employer and abides by applicable employment laws and regulations. All applicants and employees are subject to random drug testing in accordance with Executive Order 12564. Employment is contingent upon successful completion of a security background investigation and polygraph. Certification Requirements: DOD 8570 Certification This position requires an active Security Clearance with appropriate Polygraph. About us: Founded in 2007, Columbia Technology Partners is a Service-Disabled Veteran Owned Small Business with a specialization in technology and management consulting committed to solving intricate and sensitive technology issues facing corporations and federal agencies. Since its inception, CTP has been instrumental in the technical design, engineering development, operational deployment, and support of key systems. With a proven track record in information security, project management, systems/network engineering, security risk management, vulnerability assessments, and mobile security implementation; our employees have the experience, expertise, and innovative thinking our customers need for results that exceed expectations. CTP staff have worked closely with both government engineers and management to gather mission requirements, develop the architecture to deliver the needed functionality and assess tools available to meet or exceed the needs of the mission. At Columbia Technology Partners (CTP), we are united in being the best that we can be as individuals, but our core belief is that we can be better together. Together we will take on each mission with an execution process that authentically represents who we are. Our success relies on our team values, the foundation we built around them, and the Partners we become along the way. That's why our pay is competitive, our missions are critical, and our benefits represent what matters most to CTP: Our People. Salary Range Transparency At Columbia Technology Partners we are committed to transparency and fairness in our compensation practices. We believe in creating a work environment where employees feel valued, empowered, and rewarded for their contributions. How We Determine Salary Ranges Our salary ranges are based on the following key factors: Job Role and Responsibilities : The specific duties and responsibilities associated with each role form the foundation of our compensation structure. Market Research and Industry Benchmarks : We conduct regular analysis of market trends and salaries across our industry, using reliable compensation data to ensure we stay competitive. Experience and Qualifications : An individual's experience, education, certifications, and specialized skills all contribute to determining their position within a salary range. Location : Salary ranges may be adjusted based on geographic cost of living, in accordance with local and national standards. Company Performance : Our compensation practices also take into account overall company performance and financial health, ensuring that we maintain sustainability while rewarding our team. Really good benefits, for really GREAT people: From our CTP Family to yours, we know how important these decisions are. Your benefits are about you, not us. Tell us what you need in order to see a future at CTP; let's get where you're going, together . Medical: CTP offers 3 superior plans, bringing our employees both in-network and out-of-network options. Vision + Dental: Both free to you + paid in full by CTP. Retirement: 401k - 6% company contribution PTO + Leave: A work life balance is extremely important to our team here at CTP, which is why our paid time off plans are so lucrative. Offering customizable leave plans to meet your needs is just one of our many perks! Jury Duty, Bereavement + Military Leave provided. Career Growth: Up to $10,000 provided for approved career-related learning, training, education, and/or tuition. Life and AD&D Insurance/Short-Term & Long-Term Disability: More peace of mind, at zero cost to you. Profit Sharing Bonus: End of year cash gets added to your bottom-line. Referral Bonus Program: Our tiered program provides an incentive with each stage of the hiring process your referral passes. Our bonuses range from $7,000-$20,000, if your referral joins the team. Columbia Technology Partners is an Equal Opportunity Employer. We consider applicants without regard to race, color, religion, age, national origin, ancestry, ethnicity, gender, gender identity, gender expression, sexual orientation, marital status, veteran status, disability, genetic information, citizenship status, or membership in any other group protected by federal, state, or local law. Our EEO policy reflects our commitment to ensure equality and promote diversity and inclusion in the workplace. Our policy applies to all employees, job candidates, contractors, stakeholders, partners, and visitors. CTP was voted one of the top 25 best places to work in Baltimore by Baltimore Magazine!

Job Description Job Description ABOUT US Do you have a passion for higher education? Do you want to make a positive impact on the college admissions process? Our staff help to remove barriers and encourage students to forge their path to a better future. Common App is a national not-for-profit organization dedicated to the pursuit of access, equity, and integrity in the college admission process. Each year we support more than 1 million students, one-third of whom are first-generation, as they apply to our more than 1100 diverse member colleges & universities using the Common App's free online application. If you are an experienced Artificial Intelligence professional and want to be part of a mission-driven non-profit that uses innovative technology to advance the college admission process, Common App may be a great match for you. Common App is currently searching for a Principal AI & Machine Learning Engineer. RESPONSIBILITIES The Principal Artificial Intelligence (AI) & Machine Learning (ML) Engineer is the technical leader responsible for embedding artificial intelligence into enterprise workflows and analytic processes to drive measurable gains in productivity, insight generation, and decision support within the Data Analytics & Research (DAR) division. Highly regarded for exceptional performance and deep technical expertise, this role focuses on applied, production-ready AI/ML, driving groundbreaking initiatives that embed artificial intelligence into enterprise workflows Reporting to the Senior Director, Analytics Engineering, the Principal AI/ML Engineer partners closely with Data Engineering, Data Governance, and cross-functional business stakeholders to ensure that AI solutions are scalable, secure, compliant, and aligned with enterprise data strategy. This role operates as a senior individual contributor and technical authority, setting standards for AI development practice, mentoring teammates on applied AI techniques, and translating complex machine learning capabilities into enterprise-grade systems that deliver lasting organizational value. The Principal AI/ML Engineer is a recognized expert in the field, frequently sought out for technical guidance, mentorship, and thought leadership both within the organization and across the broader AI and higher education data community. Requirements QUALIFICATIONS This role requires: Candidates must live in the United States. Hybrid Work & Travel: Employees can live anywhere in the US or its territories, with the willingness and ability to travel for periodic in-person events-including semi-annual Common App retreats, department retreats, and strategic leadership sessions. Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related quantitative or technical field; or an equivalent combination of education and experience. 8-10 years of progressive experience in machine learning, AI engineering, or data science, with at least 3 years focused on applied AI and production ML systems. Demonstrated experience integrating LLMs and generative AI into enterprise analytic or operational workflows. Demonstrated experience working within enterprise data governance and compliance frameworks. Expertise in applied machine learning and AI, including supervised and unsupervised learning, natural language processing, and large language model integration (e.g., OpenAI, Anthropic, open-source LLMs via Hugging Face). Demonstrated experience designing and deploying production-grade AI/ML systems, including end-to-end ML pipelines covering training, evaluation, versioning, deployment, and monitoring. Proficiency in R and Python for machine learning and AI development; familiarity with ML frameworks such as scikit-learn, PyTorch, TensorFlow, or equivalent. Experience building and operationalizing LLM-powered applications, including prompt engineering, retrieval-augmented generation (RAG), and tool/agent orchestration frameworks. Strong SQL skills and experience working with large-scale cloud data platforms (e.g., Databricks, Snowflake, BigQuery); ability to design AI-ready data pipelines within enterprise warehouse environments. Knowledge of AI governance, responsible AI principles, and compliance considerations for AI systems handling sensitive or personally identifiable data. Proven ability to serve as a senior technical individual contributor, setting standards, making architectural decisions, and mentoring peers without formal management authority. Strong interpersonal and communication skills, with the ability to translate complex AI/ML concepts into accessible language for non-technical stakeholders and executive audiences. Proven ability to manage multiple competing priorities and deliver high-quality AI solutions in a fast-paced, collaborative environment. The ideal candidate will possess: Master's or doctoral degree in Computer Science, Machine Learning, Data Science, or a related field. Relevant AI/ML or cloud certifications (e.g., Databricks Certified Machine Learning Professional, AWS Machine Learning Specialty, or equivalent). Experience working with Agile frameworks for cross-functional, product-minded collaboration. Experience with agentic AI frameworks. Familiarity with Databricks AI features, including MLflow, Model Serving, and Genie or semantic layer integrations. Experience in higher education, nonprofit, or mission-driven technology contexts. Advanced training in statistics, causal inference, or program evaluation methods. A passion for higher education is a plus. PAY RANGE $144,160 - $162,180 Benefits Common App is a virtual first environment. We value our employees' time and efforts. Our commitment to your success is enhanced by our competitive salary and an extensive benefits package including: Work-Life balance Virtual-first office Paid Time Off (PTO) Seven company-wide holidays Nine floating holidays Sick leave Monthly mental health day floating holidays prorated depending on start date Virtual-first support Choice of PC of MAC laptop May choose an external monitor, keyboard, mouse, and/or headset One-time office set-up stipend Monthly remote work stipend Monthly mobile stipend Financial security Market-based salaries Performance-based bonus 403(b) retirement plan 5% company contribution additional 5% company match 3-year vesting schedule Participation may begin immediately Health & wellness Choice of two health insurance plans Health Savings Account, depending on health plan selection Medical Flexible Savings Account, depending on health plan selection Vision insurance Dental insurance Insurance coverage begins on the date of hire Dependent Care Flexible Spending Account Maven virtual clinic for women's and family health Company provided life and ad&d insurance Opportunity to purchase additional life insurance for self, spouse, and dependents Company provided short and long-term disability insurance Career development Budgeted annual funds for professional development Growth opportunities within the company Additional perks Mutual of Omaha Employee Assistance Program Mutual of Omaha will preparation services Mutual of Omaha travel assistance Payroll dedication pet insurance through PinPaws 1Password family account We work to maintain the best possible environment for our staff, where people can learn and grow. We strive to provide a diverse, collaborative, team-oriented, creative environment where each person feels encouraged to contribute to our processes, decisions, planning, and culture. HOW DO I APPLY To apply for this opportunity, send your resume and cover letter with salary expectations. PROTECTING YOUR PERSONAL INFORMATION: During the recruiting process, please note that Common App will never: Provide a job offer without an interview Ask for payment to process documents, purchase equipment or for any other reason Request banking or credit card information Direct you to third-party services to obtain visas or other documentation As we work alongside you through our recruitment process, please remain alert and never provide financial information or payment to anyone claiming to offer a job opportunity. If you believe you're a victim of a job scam, report it to the Federal Trade Commission (FTC) or your state attorney general. To learn more about job scams, read the FBI's public service announcement or visit the FTC site.

Vaco is partnering with a growing education technology organization to hire a Staff / Principal AI Engineer to help define and build the next generation of AI-powered products, platforms, and internal capabilities. This is a highly visible, hands-on technical leadership role focused on bringing practical AI innovation into both customer-facing products and internal business operations. This person will serve as a technical change leader as the organization moves toward broader use of AI agents, generative AI, machine learning, and LLM-powered product experiences. The right candidate will bring strong architecture and engineering depth, but also a product mindset. This role is about building real solutions, teaching teams how to use AI effectively, securing AI-enabled workflows, and identifying where AI can improve customer experience, training products, marketing funnels, and business outcomes. What You'll Be Doing Lead the design, development, and deployment of scalable AI and machine learning solutions across product and internal business use cases Architect generative AI systems, LLM-powered workflows, agentic solutions, and AI-enabled product features Build and optimize LLMOps pipelines that support reliable deployment, evaluation, monitoring, and iteration of AI models Partner with product, architecture, data, engineering, innovation, and marketing teams to identify where AI can create measurable business impact Drive AI innovation within customer-facing products, training platforms, digital experiences, and lead conversion workflows Evaluate and implement approaches for prompt engineering, context management, embeddings, retrieval, and model optimization Design AI systems with feedback loops, automated retraining, fine-tuning, and lifecycle management where appropriate Build data pipelines and preprocessing workflows that ensure data quality, security, and regulatory alignment Provide hands-on technical leadership through architecture reviews, code contributions, proof-of-concepts, and implementation guidance Mentor AI engineers and partner with architects across application, product, CRM, and data domains Help establish standards, documentation, and best practices for responsible AI development and deployment Stay current on emerging AI trends, including AI's impact on digital marketing, Answer Engine Optimization, Generative Engine Optimization, and customer discovery behavior Required Experience 8 or more years of progressive experience across software engineering, data, analytics, machine learning, AI engineering, or related technology roles 1 or more years of experience developing and implementing analytical, AI, or machine learning applications Hands-on experience building and deploying LLM-based solutions, generative AI applications, or AI-powered product features Strong understanding of machine learning, natural language processing, large language models, embeddings, retrieval patterns, and model evaluation Experience with Python, SQL, Hugging Face, Snowflake, and modern ML or analytics tooling Experience designing AI or ML solutions in Azure or comparable cloud environments Experience with CI/CD pipelines, Docker, Kubernetes, MLflow, or similar MLOps and lifecycle management tools Ability to translate ambiguous AI opportunities into practical, scalable engineering solutions Strong product mindset with interest in customer experience, product innovation, marketing enablement, and business impact Demonstrated ability to mentor engineers, influence technical direction, and guide best practices Strong communication skills with the ability to present complex AI concepts to technical and non-technical stakeholders Bachelor's degree in Computer Science, Artificial Intelligence, or a related field preferred, or equivalent professional experience Nice to Have Experience building AI agents or agentic workflows for internal business operations Exposure to AI security, responsible AI, model governance, or securing AI-enabled systems Experience applying AI to online shopping, customer acquisition, digital marketing, or lead conversion workflows Familiarity with Answer Engine Optimization or Generative Engine Optimization concepts Experience with Azure AI services or comparable cloud AI platforms Background working in education technology, training platforms, eCommerce, or digital learning environments Experience helping organizations adopt AI tools, workflows, and operating models across multiple teams Compensation & Benefits Salary range: $170,000 to $190,000 annually Full-time role with benefits package available If you are a hands-on AI engineering leader who wants to build practical generative AI systems, shape product innovation, and help an organization move from AI experimentation to real enterprise adoption, we would welcome the opportunity to connect. Determining compensation for this role (and others) at Vaco/Highspring depends upon a wide array of factors including but not limited to the individual's skill sets, experience and training, licensure and certifications, office location and other geographic considerations, as well as other business and organizational needs. With that said, as required by local law in geographies that require salary range disclosure, Vaco/Highspring notes the salary range for the role is noted in this job posting. The individual may also be eligible for discretionary bonuses, and can participate in medical, dental, and vision benefits as well as the company's 401(k) retirement plan. Additional disclaimer: Unless otherwise noted in the job description, the position Vaco/Highspring is filing for is occupied. Please note, however, that Vaco/Highspring is regularly asked to provide talent to other organizations. By submitting to this position, you are agreeing to be included in our talent pool for future hiring for similarly qualified positions. Submissions to this position are subject to the use of AI to perform preliminary candidate screenings, focused on ensuring minimum job requirements noted in the position are satisfied. Further assessment of candidates beyond this initial phase within Vaco/Highspring will be otherwise assessed by recruiters and hiring managers. Vaco/Highspring does not have knowledge of the tools used by its clients in making final hiring decisions and cannot opine on their use of AI products. EEO Notice Vaco by Highspring is an Equal Opportunity Employer and does not discriminate against any employee or applicant for employment because of race (including but not limited to traits historically associated with race such as hair texture and hair style), color, sex (includes pregnancy or related conditions), religion or creed, national origin, citizenship, age, disability, status as a veteran, union membership, ethnicity, gender, gender identity, gender expression, sexual orientation, marital status, political affiliation, or any other protected characteristics as required by federal, state or local law. Vaco by Highspring and its parents, affiliates, and subsidiaries are committed to the full inclusion of all qualified individuals. As part of this commitment, Vaco by Highspring and its parents, affiliates, and subsidiaries will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact . Vaco by Highspring also wants all applicants to know their rights that workplace discrimination is illegal. Representation Notice By submitting to this position, you agree that you will be giving Vaco by Highspring the exclusive right to present your as a candidate for the foregoing employment opportunity. You further agree that you have represented information about yourself accurately and have not affirmatively misrepresented your qualifications. You also agree to maintain as confidential, to the fullest extent permitted by law, any information you learn from Vaco by Highspring about the position and you will limit disclosure of information about the position only to the extent necessary to perform any obligations in furtherance of your application. In exchange, Vaco by Highspring agrees to exercise reasonable efforts to represent you through all solicitation, job screening and resume dispersal. For residents of Ontario, Canada: Based on Highspring's discussions with its Client, Highspring's understanding is that this position for employment is a current vacancy (either through Highspring as a contractor or with the client directly). Privacy Notice Vaco by Highspring and its parents, affiliates, and subsidiaries ("we," "our," or "Vaco by Highspring") respects your privacy and are committed to providing transparent notice of our policies. California residents may access Vaco by Highspring HR Notice at Collection for California Applicants and Employees here. Virginia residents may access our state specific policies here. Residents of all other states may access our policies here. Canadian residents may access our policies in English here and in French here. Residents of countries governed by GDPR may access our policies here. Additionally, submissions to this position are subject to the use of AI to perform preliminary candidate screenings, focused on ensuring minimum job requirements noted in the position are satisfied. More details about Vaco by Highspring's use of AI can be found here (). Further assessment of candidates beyond this initial phase will be conducted by recruiters and hiring managers. Vaco by Highspring does not know and cannot opine on if its client's use of AI products in hiring . click apply for full job details

Job Family: Data Science Consulting Travel Required: Up to 10% Clearance Required: Active Public Trust What You Will Do: The Border Security AI/ML Engineer will join a dynamic team supporting U.S Federal border security customers. In this role, the candidate will collaborate with border security and law enforcement clients to design develop and deploy AI and ML applications to support mission outcomes. Develop optimized ML tool sets and applications aligned to customer use cases Develop and maintain data governance documentation, tools, and templates. Coordinate with non-technical users to gather requirements. Support key mission clients within the Washington DC Metro region at client sites. We are actively hiring for this role at multiple levels (Associate, Senior, and Lead) to support ongoing and upcoming federal client work across CBP. Candidates will be considered and leveled based on experience, technical capabilities, and overall alignment to project needs. What You Will Need: An ACTIVE and MAINTAINED CBP PUBLIC TRUST OR an ACTIVE and MAINTAINED "TOP SECRET" Federal or DoD security clearance. Bachelors Degree. Experience designing and implementing machine learning algorithms and artificial intelligence solutions Experience deploying Machine Learning solutions within cloud environments including AWS and/or Google Experience configuring AI applications for law enforcement use cases What Would Be Nice To Have: Experience working with COTS data tools such as DataRobot Proficiency working with CSP platforms and tools such as AWS Sagemaker and Rekognition, Google Cloud Platform and Google AI tools Experience developing bespoke analytical tools for law enforcement analysis Direct Experience supporting the National Targeting Center or similar National Security analysis fusion centers What We Offer: Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace. Benefits include: Medical, Rx, Dental & Vision Insurance Personal and Family Sick Time & Company Paid Holidays Position may be eligible for a discretionary variable incentive bonus Parental Leave and Adoption Assistance 401(k) Retirement Plan Basic Life & Supplemental Life Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts Short-Term & Long-Term Disability Student Loan PayDown Tuition Reimbursement, Personal Development & Learning Opportunities Skills Development & Certifications Employee Referral Program Corporate Sponsored Events & Community Outreach Emergency Back-Up Childcare Program Mobility Stipend About Guidehouse Guidehouse is an Equal Opportunity Employer-Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation. Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco. If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse 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 accommodation. All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains or . Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process. If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse's Ethics Hotline. If you want to check the validity of correspondence you have received, please contact . Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant's dealings with unauthorized third parties. Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.

Sr. 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. What You'll Do: 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, agents and multi-agent workflows, 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, PyTorch, and more. Invent and introduce state-of-the-art foundation model 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. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership 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, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 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 AI systems Demonstrated ability to lead and mentor multiple engineering teams 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, CUDA, 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 Experience in building agentic AI systems and agentic workflows 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 Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff 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 (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. What You'll Do: 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, agents and multi-agent workflows, 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, PyTorch, and more. Invent and introduce state-of-the-art foundation model 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. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership. Capital One is open to hiring a Remote Employee for this opportunity. 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, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 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 AI systems Demonstrated ability to lead and mentor multiple engineering teams 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, CUDA, 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 Experience in building agentic AI systems and agentic workflows 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 Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff 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. What You'll Do: 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, agents and multi-agent workflows, 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, PyTorch, and more. Invent and introduce state-of-the-art foundation model 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. Set the technical direction for enterprise-wide AI architecture - unifying tooling, observability, and deployment standards across teams Own the design and integration of model routing, caching, and orchestration systems that support hybrid and multi-model workloads Champion responsible AI principles across all system design, embedding transparency, reproducibility, and fairness-by-design Drive internal education, mentorship, and dissemination of best practices through architecture councils and AI guilds 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 enables 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, 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, CUDA, or Java Preferred Qualifications: Experience designing AI systems with tradeoff decisions around cost, latency, throughput and accuracy 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, CUDA, 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 Experience in building agentic AI systems and agentic workflows 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 Proven track record of defining and operationalizing enterprise AI architecture standards, including data pipeline governance, observability and evaluation frameworks Experience leading federated or multi-cloud AI strategies to maximize resilience, compliance and compute efficiency Demonstrated success influencing research-to-production promotion processes - guiding model handoff, evaluation and productization Experience defining north-star metrics for AI systems that balance business value, innovation velocity, cost, and ethical responsibility Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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 Staff AI Engineer Cambridge, MA: $269,100 - $307,200 for Staff AI Engineer McLean, VA: $269,100 - $307,200 for Staff AI Engineer New York, NY: $293,600 - $335,100 for Staff AI Engineer San Francisco, CA: $293,600 - $335,100 for Staff AI Engineer San Jose, CA: $293,600 - $335,100 for Staff 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. . click apply for full job details

Sr. 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. What You'll Do: 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, agents and multi-agent workflows, 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, PyTorch, and more. Invent and introduce state-of-the-art foundation model 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. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership 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, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 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 AI systems Demonstrated ability to lead and mentor multiple engineering teams 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, CUDA, 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 Experience in building agentic AI systems and agentic workflows 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 Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff 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 - 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. Capital One is open to hiring a Remote Employee for this opportunity What You'll Do: 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, agents and multi-agent workflows, 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, PyTorch, and more. Invent and introduce state-of-the-art foundation model 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. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership 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, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 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 AI systems Demonstrated ability to lead and mentor multiple engineering teams 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, CUDA, 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 Experience in building agentic AI systems and agentic workflows 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 Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff 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 - 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. What You'll Do: 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, agents and multi-agent workflows, 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, PyTorch, and more. Invent and introduce state-of-the-art foundation model 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. Set the technical direction for enterprise-wide AI architecture - unifying tooling, observability, and deployment standards across teams Own the design and integration of model routing, caching, and orchestration systems that support hybrid and multi-model workloads Champion responsible AI principles across all system design, embedding transparency, reproducibility, and fairness-by-design Drive internal education, mentorship, and dissemination of best practices through architecture councils and AI guilds 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 enables 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, 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, CUDA, or Java Preferred Qualifications: Experience designing AI systems with tradeoff decisions around cost, latency, throughput and accuracy 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, CUDA, 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 Experience in building agentic AI systems and agentic workflows 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 Proven track record of defining and operationalizing enterprise AI architecture standards, including data pipeline governance, observability and evaluation frameworks Experience leading federated or multi-cloud AI strategies to maximize resilience, compliance and compute efficiency Demonstrated success influencing research-to-production promotion processes - guiding model handoff, evaluation and productization Experience defining north-star metrics for AI systems that balance business value, innovation velocity, cost, and ethical responsibility Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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 Staff AI Engineer Cambridge, MA: $269,100 - $307,200 for Staff AI Engineer McLean, VA: $269,100 - $307,200 for Staff AI Engineer New York, NY: $293,600 - $335,100 for Staff AI Engineer San Francisco, CA: $293,600 - $335,100 for Staff AI Engineer San Jose, CA: $293,600 - $335,100 for Staff 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 . click apply for full job details

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. What You'll Do: 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, agents and multi-agent workflows, 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, PyTorch, and more. Invent and introduce state-of-the-art foundation model 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. Set the technical direction for enterprise-wide AI architecture - unifying tooling, observability, and deployment standards across teams Own the design and integration of model routing, caching, and orchestration systems that support hybrid and multi-model workloads Champion responsible AI principles across all system design, embedding transparency, reproducibility, and fairness-by-design Drive internal education, mentorship, and dissemination of best practices through architecture councils and AI guilds. 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 enables 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, 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, CUDA, or Java Preferred Qualifications: Experience designing AI systems with tradeoff decisions around cost, latency, throughput and accuracy 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, CUDA, 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 Experience in building agentic AI systems and agentic workflows 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 Proven track record of defining and operationalizing enterprise AI architecture standards, including data pipeline governance, observability and evaluation frameworks Experience leading federated or multi-cloud AI strategies to maximize resilience, compliance and compute efficiency Demonstrated success influencing research-to-production promotion processes - guiding model handoff, evaluation and productization Experience defining north-star metrics for AI systems that balance business value, innovation velocity, cost, and ethical responsibility Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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 Staff AI Engineer Cambridge, MA: $269,100 - $307,200 for Staff AI Engineer McLean, VA: $269,100 - $307,200 for Staff AI Engineer New York, NY: $293,600 - $335,100 for Staff AI Engineer San Francisco, CA: $293,600 - $335,100 for Staff AI Engineer San Jose, CA: $293,600 - $335,100 for Staff 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. . click apply for full job details

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. What You'll Do: 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, agents and multi-agent workflows, 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, PyTorch, and more. Invent and introduce state-of-the-art foundation model 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. Set the technical direction for enterprise-wide AI architecture - unifying tooling, observability, and deployment standards across teams Own the design and integration of model routing, caching, and orchestration systems that support hybrid and multi-model workloads Champion responsible AI principles across all system design, embedding transparency, reproducibility, and fairness-by-design Drive internal education, mentorship, and dissemination of best practices through architecture councils and AI guilds 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 enables 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, 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, CUDA, or Java Preferred Qualifications: Experience designing AI systems with tradeoff decisions around cost, latency, throughput and accuracy 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, CUDA, 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 Experience in building agentic AI systems and agentic workflows 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 Proven track record of defining and operationalizing enterprise AI architecture standards, including data pipeline governance, observability and evaluation frameworks Experience leading federated or multi-cloud AI strategies to maximize resilience, compliance and compute efficiency Demonstrated success influencing research-to-production promotion processes - guiding model handoff, evaluation and productization Experience defining north-star metrics for AI systems that balance business value, innovation velocity, cost, and ethical responsibility Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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 Staff AI Engineer Cambridge, MA: $269,100 - $307,200 for Staff AI Engineer McLean, VA: $269,100 - $307,200 for Staff AI Engineer New York, NY: $293,600 - $335,100 for Staff AI Engineer San Francisco, CA: $293,600 - $335,100 for Staff AI Engineer San Jose, CA: $293,600 - $335,100 for Staff 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 . click apply for full job details

Sr. 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. What You'll Do: 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, agents and multi-agent workflows, 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, PyTorch, and more. Invent and introduce state-of-the-art foundation model 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. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Capital One is open to hiring a Remote Employee for this opportunity. 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, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 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 AI systems Demonstrated ability to lead and mentor multiple engineering teams 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, CUDA, 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 Experience in building agentic AI systems and agentic workflows 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 Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff 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. What You'll Do: 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, agents and multi-agent workflows, 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, PyTorch, and more. Invent and introduce state-of-the-art foundation model 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. Set the technical direction for enterprise-wide AI architecture - unifying tooling, observability, and deployment standards across teams Own the design and integration of model routing, caching, and orchestration systems that support hybrid and multi-model workloads Champion responsible AI principles across all system design, embedding transparency, reproducibility, and fairness-by-design Drive internal education, mentorship, and dissemination of best practices through architecture councils and AI guilds 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 enables 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, 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, CUDA, or Java Preferred Qualifications: Experience designing AI systems with tradeoff decisions around cost, latency, throughput and accuracy 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, CUDA, 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 Experience in building agentic AI systems and agentic workflows 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 Proven track record of defining and operationalizing enterprise AI architecture standards, including data pipeline governance, observability and evaluation frameworks Experience leading federated or multi-cloud AI strategies to maximize resilience, compliance and compute efficiency Demonstrated success influencing research-to-production promotion processes - guiding model handoff, evaluation and productization Experience defining north-star metrics for AI systems that balance business value, innovation velocity, cost, and ethical responsibility Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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 Staff AI Engineer Cambridge, MA: $269,100 - $307,200 for Staff AI Engineer McLean, VA: $269,100 - $307,200 for Staff AI Engineer New York, NY: $293,600 - $335,100 for Staff AI Engineer San Francisco, CA: $293,600 - $335,100 for Staff AI Engineer San Jose, CA: $293,600 - $335,100 for Staff 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. . click apply for full job details