AI Engineer 5

Capital One Financial

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Quick summary

Work type: On-site
Location: McLean, VASan Francisco, CACambridge, MASan Jose, CANew York, NY
Employment: Full-time
Posted: 12 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $217k

$178k $271k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $186,900–$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 1917 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1045 roles with salary data.

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At a glance

TL;DR · AI Engineer 5

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The AI Engineer 5 (MLX) joins the Intelligent Foundations and Experiences team to develop proprietary AI solutions that power core business functions and customer interactions. This role involves designing, developing, testing, and deploying 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, optimize performance for scalability and cost, and lead technical design councils to ensure engineering standards. The position requires proficiency in Python, Go, Scala, CUDA, or Java, alongside experience with PyTorch, Huggingface, VectorDBs, and AWS Ultraclusters. You will solve complex problems regarding model throughput, latency, and inference cost efficiency while mentoring other engineers to elevate organizational technical maturity within a high-performance production AI infrastructure.

What does a AI Engineer earn in Virginia?

Median $246150 from 59 postings across 4 companies.

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Skills

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

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 scalability, cost, latency, and throughput of production AI.
Establish and lead cost-performance governance reviews tracking 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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