Lead AI Engineer

Capital One Financial

Confirmed live yesterday Low trust

Quick summary

Work type: On-site
Location: San Francisco, CAMcLean, VACambridge, MASan Jose, CANew York, NY
Employment: Full-time
Posted: 60 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $204k

$141k $257k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $162,000–$246,150.

Based on 240 similar postings.

Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 2107 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1107 roles with salary data.

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At a glance

TL;DR · Lead AI Engineer

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The Lead AI Engineer (Gen AI Platform Services: Agentic AI, Agent Guardrails, Agent Evaluation, Agent Memory) joins the Intelligent Foundations and Experiences team to build and deploy proprietary AI solutions. You will partner with cross-functional teams to design, develop, test, and support AI software components, including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves inventing state-of-the-art LLM optimization techniques to improve performance, scalability, cost, latency, and throughput for large-scale production systems. You will utilize a technical stack including AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, Python, Go, Scala, and Java. This position addresses the technical challenge of creating responsible, scalable, and high-performance AI infrastructure to power banking products and internal workflows.

Skills

Python Go Scala Java C++ C# PyTorch Huggingface AWS Google Cloud Azure VectorDBs Nemo Guardrails LLM Inference Similarity Search Machine Learning

What you'll do

Design, develop, test, deploy, and support AI software components including foundation model training and LLM inference.
Implement similarity search, guardrails, model evaluation, experimentation, governance, and observability systems.
Utilize open-source and SaaS technologies including AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch.
Develop state-of-the-art LLM optimization techniques to improve scalability, cost, latency, and throughput.
Contribute to the technical vision and long-term roadmap of foundational AI systems.
Apply novel techniques from scientific publications to production AI environments.
Build and deploy proprietary AI solutions that deliver value to millions of customers.

What we're looking for

Bachelor'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.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms.
At least 4 years of experience programming with Python, Go, Scala, or Java.
6 years of experience deploying scalable and responsible AI solutions on cloud platforms (preferred).
Experience designing, developing, delivering, and supporting AI services (preferred).
Experience developing AI and ML algorithms or technologies using Python, C++, C#, Java, or Golang (preferred).
Experience developing and applying state-of-the-art techniques for optimizing training and inference software (preferred).
Passion for staying abreast of the latest AI research and judiciously applying novel techniques in production (preferred).

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