AI Engineer (MLX)

Requirements:

• Bachelors degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field and at least 4 years of experience developing AI/ML algorithms or technologies; or a relevant masters degree and at least 2 years of such experience.
• At least 4 years of programming experience with Python, Go, Scala, CUDA, or Java.
• Preferred: Experience leading AI system development and making tradeoffs among cost, latency, throughput, and accuracy.
• Preferred: At least 6 years deploying scalable, responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud.
• Preferred: Experience designing, developing, delivering, and supporting AI services.
• Preferred: Experience building AI/ML algorithms or technologies, such as LLM inference, similarity search, vector databases, guardrails, or memory, using Python, C++, C#, Java, CUDA, or Golang.
• Preferred: Experience optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
• Preferred: Experience building agentic AI systems and workflows.
• Preferred: Knowledge of current AI research and experience applying suitable techniques in production.
• Preferred: Proficiency in distributed systems for model training, evaluation, and online inference at petabyte scale.
• Preferred: Experience defining AI model governance processes, including producibility, lineage tracking, and automated retraining schedules.
• Preferred: Ability to influence architecture decisions across multiple AI products or platforms.
• Ideal candidates bring strong engineering and mathematical foundations, technical depth across hardware, software, and AI, adaptability in ambiguous situations, curiosity, clear communication, resilience, and a commitment to responsible work.

Responsibilities:

• Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products for associates and customers.
• Design, develop, test, deploy, and support AI software components, including foundation-model training, LLM inference, agent and multi-agent workflows, similarity search, guardrails, evaluation, experimentation, governance, and observability.
• Use open-source and SaaS AI technologies, including AWS Ultraclusters, Hugging Face, vector databases, and PyTorch.
• Develop advanced foundation-model optimization techniques to improve scalability, cost, latency, and throughput in production systems.
• Help shape the technical vision and long-term roadmap for foundational AI systems.
• Own end-to-end architecture for complex AI systems, supporting maintainability, observability, and ethical alignment.
• Define and maintain reliability service-level objectives, including latency, uptime, and model-performance drift.
• Work with infrastructure engineering to improve GPU/TPU utilization and accelerate inference pipelines.
• Lead technical reviews of AI deployments to ensure security, data governance, and compliance standards are met.
• Mentor Principal and Senior Associates in scalable design, performance tuning, and moving research into production.

Technologies:

• Agentic AI
• AI
• AWS
• Azure
• C#
• Cloud
• CUDA
• Golang
• Hardware
• Support
• Java
• LLM
• Machine Learning
• Model Training
• PyTorch
• Python
• Scala
• Security

More

We are Capital One, where we build responsible, reliable AI systems to improve banking. Our investments in technology, machine learning, and experienced teams support personalized customer experiences and scalable AI capabilities. The Intelligent Foundations and Experiences (IFX) team works with partners across the company to advance AI science and engineering and deliver proprietary models and platforms used by teams serving millions of customers. This AI Engineer 4 role is available in Cambridge, MA; McLean, VA; New York, NY; San Francisco, CA; and San Jose, CA. Listed annual salary ranges are $197,300–$225,100 in Cambridge and McLean and $215,200–$245,600 in New York, San Francisco, and San Jose; pay varies by work location. The role may also include performance-based incentives and is eligible for our health, financial, and other benefits, subject to eligibility. We are an equal opportunity employer and will consider sponsoring a qualified applicant for employment authorization.

last updated 43 week of 2026