AI Engineer 4 (AI Foundations: LLM Customization, Finetuning, Reinforcement Learning)
Capital One2 days ago
Cambridge, MA, USA +3 moreStaff+
Base Salary
$215k - $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 components including foundation model training, LLM inference, agents, multi-agent workflows, similarity search, guardrails, evaluation, experimentation, governance, and observability.
- Develop foundation model optimization techniques to improve scalability, cost, latency, throughput, and production performance.
- Own end-to-end architecture for complex AI systems and contribute to the long-term technical roadmap.
- Define and maintain AI reliability objectives covering latency, uptime, and model performance drift.
- Optimize GPU and TPU utilization and accelerate model inference pipelines with infrastructure engineering teams.
- Lead technical reviews for AI deployments, ensuring security, data governance, compliance, and ethical standards.
- Mentor senior and principal 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 a related field plus at least two years of such 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 AWS, Google Cloud, Azure, or equivalent private cloud, including six years of cloud AI experience.
- Experience designing, delivering, and supporting AI services and optimizing training and inference software.
- Experience with LLM inference, similarity search, vector databases, guardrails, memory, agentic AI systems, and agentic workflows.
- Experience designing distributed systems for model training, evaluation, and online inference at petabyte scale.
- Experience defining AI model governance processes, including lineage tracking and automated retraining schedules.
- Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms.
Benefits
- Eligible for performance-based incentive compensation, including cash bonuses and/or long-term incentives.
- Comprehensive health, financial, and other benefits supporting total well-being, with eligibility varying by employment status and management level.
- Full-time role with location-specific annual salary ranges; applications accepted for a minimum of five business days.
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.