Lead Machine Learning Engineer

Capital One Financial

Confirmed live today Low trust

Quick summary

Work type: On-site
Location: Cambridge, MAMcLean, VARichmond, VA
Employment: Full-time
Posted: 89 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 $228k

$173k $289k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $200,437–$254,750.

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 Machine Learning Engineer

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The Lead Machine Learning Engineer joins the Risk Tech team to build and deploy proprietary risk management solutions powered by state-of-the-art AI technology. Working with the GRC team, you will design, develop, test, and support AI software components, including large language model inference, similarity search, guardrails, and agentic AI. You will fine-tune foundation models, construct optimized data pipelines, and monitor production models while ensuring adherence to Responsible and Explainable AI practices. The role requires proficiency in Python, Scala, or Java, along with experience in frameworks like scikit-learn, PyTorch, Dask, Spark, or TensorFlow. You will also utilize tools such as AWS Bedrock, Google Cloud, or Azure. This position solves critical business problems by creating data-driven tools to prevent risks and automatically detect issues before they impact customers.

Skills

Python Scala Java PyTorch TensorFlow scikit-learn Spark Dask AWS Bedrock Google Cloud Azure RAG Distributed Computing Data Pipelines Agile Explainable AI

What you'll do

Design, develop, test, and deploy AI software components including LLM inference and similarity search.
Fine-tune, develop, and evaluate machine learning and foundation models for production use.
Construct and optimize data pipelines to feed machine learning models.
Retrain, maintain, and monitor models in production environments.
Ensure all code follows best practices for Responsible and Explainable AI and risk governance.
Provide technical vision and thought leadership for the long-term AI systems roadmap.
Leverage open-source and SaaS AI technologies to build proprietary risk management solutions.

What we're looking for

At least 6 years of experience designing and building data-intensive solutions using distributed computing.
At least 4 years of experience programming with Python, Scala, or Java.
At least 2 years of experience building, scaling, and optimizing ML systems.
Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field (preferred).
7+ years of experience designing, developing, delivering, and supporting AI services at scale (preferred).
3+ years of experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow (preferred).
2+ years of experience with Retrieval Augmented Generation (RAG) (preferred).

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