AI Engineer 5

Capital One Financial

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Quick summary

Work type: On-site
Location: San Jose, CANew York, NYCambridge, MA
Salary: $229,900–$262,400 / yr
Employment: Full-time
Posted: 13 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $215k

This role $246k

$175k $272k

below market most similar roles pay here above market

This role pays more than 85% of similar roles. Most pay $184,300–$246,150 — the blue band above. At the midpoint, this role pays about $246k versus about $215k for comparable roles.

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.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · AI Engineer 5

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The AI Engineer 5 joins the Intelligent Foundations and Experiences team to develop and deploy proprietary AI solutions that power core business functions and customer interactions. This role involves designing, testing, and supporting AI software components, including foundation model training, large language model inference, multi-agent workflows, similarity search, and guardrails. You will build multi-model orchestration pipelines and optimize performance regarding scalability, cost, and latency. The technical stack includes Python, Go, Scala, CUDA, Java, PyTorch, Huggingface, VectorDBs, and AWS Ultraclusters. You will also lead cost-performance governance reviews and mentor other engineers. The work focuses on creating responsible, scalable AI infrastructure to solve complex banking problems, such as providing real-time personalized customer experiences and identifying unusual charges through advanced machine learning and generative AI technologies.

What does a AI Engineer earn in California?

Median $246150 from 100 postings across 17 companies.

See salary data

Skills

Python Go Scala CUDA Java C++ C# PyTorch Huggingface AWS Google Cloud Azure VectorDBs LLM Inference Similarity Search Multi-agent workflows Model Evaluation Observability Model Compression

What you'll do

Design, develop, test, deploy, and support AI software components including foundation model training and LLM inference.
Implement multi-model orchestration pipelines integrating LLMs, vector search, and domain-specific models into unified systems.
Invent and introduce state-of-the-art optimization techniques to improve performance, scalability, cost, and latency of production AI.
Establish and lead cost-performance governance reviews to track GPU utilization, model throughput, and inference cost efficiency.
Lead team design councils to ensure technical consistency and compliance with AI engineering standards.
Mentor Principal and Manager-level AI engineers to foster cross-domain learning and elevate organizational technical maturity.
Contribute to the technical vision and long-term roadmap of foundational AI systems.

What we're looking for

Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 6 years of experience developing AI and ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 4 years of experience developing AI and ML algorithms.
At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java.
Experience leading development of AI systems with tradeoff decisions around cost, latency, throughput, and accuracy (preferred).
7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (preferred).
Experience designing, developing, delivering, and supporting complex AI systems (preferred).
Experience developing AI and ML algorithms using Python, C++, C#, Java, CUDA, or Golang (preferred).
Experience developing and applying state-of-the-art techniques for optimizing training and inference software (preferred).

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