AI Engineer 4

Capital One Financial

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Quick summary

Work type: On-site
Location: New York, NYSan Francisco, CAMcLean, VACambridge, MASan Jose, CA
Salary: $197,300–$225,100 / 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 $202k

This role $211k

$187k $230k

below market most similar roles pay here above market

This role pays more than 80% of similar roles. Most pay $192,050–$211,200 — the blue band above. At the midpoint, this role pays about $211k versus about $202k 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 1917 open roles on FindRole.

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

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · AI Engineer 4

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The AI Engineer 4 (MLX) joins the Intelligent Foundations and Experiences team to develop and deploy proprietary AI solutions central to the business. This role involves designing, developing, testing, and supporting AI software components, including foundation model training, large language model inference, agents, multi-agent workflows, similarity search, guardrails, and model evaluation. The engineer will invent optimization techniques to improve performance, scalability, cost, latency, and throughput for large-scale production systems. Key responsibilities include owning end-to-end architecture, defining service-level objectives, and collaborating with infrastructure teams to optimize GPU/TPU utilization. Required technologies and skills include Python, Go, Scala, CUDA, Java, C#, C++, PyTorch, Huggingface, VectorDBs, and AWS Ultraclusters. The work focuses on building responsible, scalable AI infrastructure to solve complex banking problems and enhance customer interactions.

What does a AI Engineer earn in New York?

Median $245450 from 61 postings across 10 companies.

See salary data

Skills

Python Go Scala CUDA Java C++ C# PyTorch Huggingface AWS Google Cloud Azure VectorDBs LLM Inference Distributed Systems Model Evaluation Observability GPU TPU

What you'll do

Design, develop, test, deploy, and support AI software components including foundation model training and LLM inference.
Build and manage agents, multi-agent workflows, similarity search, guardrails, and model evaluation systems.
Implement foundation model optimization techniques to improve scalability, cost, latency, and throughput of production systems.
Own the end-to-end architecture for complex AI systems to ensure maintainability, observability, and ethical alignment.
Define and maintain service-level objectives for AI reliability, including latency, uptime, and model performance drift.
Optimize GPU/TPU utilization and accelerate model inference pipelines in collaboration with infrastructure engineering.
Lead cross-functional technical reviews to ensure new AI deployments meet security, data governance, and compliance standards.
Mentor senior associates on scalable design, performance tuning, and translating research into production environments.

What we're looking for

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related field plus 4 years of AI/ML experience.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related field plus 2 years of AI/ML experience.
At least 4 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).
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 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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