Senior Lead AI Engineer(MLX, Agentic AI, Gen AI platform Services)

About the role

You will 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.

Responsibilities

• Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, 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, Nemo Guardrails, PyTorch, and more.
• Invent and introduce state-of-the-art LLM 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.

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 enable you to see and exploit optimization opportunities that others miss.
• You are a resilient trail blazer 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 6 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 4 years of experience developing AI and ML algorithms or technologies
• At least 6 years of experience programming with Python, Go, Scala, or Java

Preferred qualifications

• 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
• Experience designing, developing, integrating, delivering, and supporting complex AI systems
• Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders
• Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, 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
• 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

Pay

• McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer
• Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer
• New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer
• San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer
• San Jose, CA: $250,800 - $286,200 for Sr. Lead 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.