AI Engineer 4 (MLX, Agentic AI, Gen AI platform Services)
Capital One1 day ago
Cambridge, MA, USA +4 moreStaff+
Base Salary
$197k - $246k/yr
Responsibilities
- 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 for large-scale production AI systems to improve scalability, cost, latency, throughput, and hardware utilization.
- Own end-to-end architectures for complex AI systems and contribute to the technical vision and long-term roadmap of foundational AI platforms.
- 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 and ensure security, data governance, compliance, maintainability, and ethical alignment.
- 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 4 years of experience developing AI and ML algorithms or technologies, or a relevant master's degree plus at least 2 years of that experience.
- At least 4 years of programming experience with Python, Go, Scala, CUDA, or Java.
- Preferred experience leading AI-system development with tradeoff decisions involving cost, latency, throughput, and accuracy.
- Preferred 6 years of experience deploying scalable and responsible AI solutions on AWS, Google Cloud, Azure, or an equivalent private cloud.
- Experience developing and supporting AI services, agentic AI systems, agentic workflows, and AI/ML technologies such as LLM inference, similarity search, VectorDBs, guardrails, and memory.
- Experience optimizing training and inference software and 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 and apply current AI research in production.
Benefits
- Capital One offers health, financial, and other benefits supporting total well-being, with eligibility varying by employment status and management level.
- The role is eligible for performance-based incentive compensation, including potential cash bonuses and long-term incentives.
- The position is available in Cambridge, McLean, New York, San Francisco, and San Jose, with compensation varying by work location.
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
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.