AI Engineer 4 (AI Foundations: Benchmarking, Evaluation, and Explainability)
Capital One1 day ago
Cambridge, MA, USA +3 moreStaff+
Base Salary
$197k - $246k/yr
Responsibilities
- Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products.
- Design, develop, test, deploy, and support AI software components including foundation model training, LLM inference, agents, multi-agent workflows, similarity search, guardrails, evaluation, experimentation, governance, and observability.
- Develop optimization techniques to improve the scalability, cost, latency, throughput, and performance of large-scale production AI systems.
- Own the end-to-end architecture and long-term roadmap for foundational AI systems.
- Define and maintain service-level objectives for AI reliability, including latency, uptime, and model performance drift.
- Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines.
- Lead technical reviews for AI deployments, ensuring security, data governance, compliance, and ethical standards are met.
- Mentor Principal and Senior Associates on scalable design, performance tuning, and research-to-production translation.
Requirements
- Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field plus at least four years of experience developing AI and ML algorithms or technologies, or a master's degree in one of these fields plus at least two years of relevant experience.
- At least four years of programming experience with Python, Go, Scala, CUDA, or Java.
- Experience leading AI system development with tradeoff decisions involving cost, latency, throughput, and accuracy.
- Preferred experience deploying scalable and responsible AI solutions on cloud platforms, including six or more years of experience preferred.
- Experience designing, developing, delivering, and supporting AI services.
- Experience with LLM inference, similarity search, vector databases, guardrails, or memory using Python, C++, C#, Java, CUDA, or Go.
- Experience optimizing training and inference software for hardware utilization, latency, throughput, and cost.
- Experience building agentic AI systems and workflows.
- Proficiency designing distributed systems for model training, evaluation, and online inference at petabyte scale.
- Experience defining AI model governance processes, including producibility, lineage tracking, and automated retraining schedules.
- Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms.
- Strong engineering, mathematical, hardware, software, AI, and technical research skills.
Benefits
- Capital One offers comprehensive health, financial, and other benefits supporting total well-being, with eligibility varying by employment status and management level.
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
- The role is eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.
About Capital One
Capital One is a U.S. consumer and commercial bank that offers credit cards, checking and savings accounts, auto financing, and lending to small and large businesses. It earns revenue from interest income and interchange/fees across its card and banking products, and develops cloud-based digital services. Founded in 1994, Capital One is publicly traded on the NYSE (COF) and is headquartered in McLean, Virginia.