Lead Machine Learning Engineer (Manager IC)

Capital One Financial

Quick summary

Work type: On-site
Location: McLean, VACambridge, MASan Jose, CANew York, NY
Salary: $197,300–$225,100 / yr
Posted: 6 days ago
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $224k

This role $211k

$171k most similar roles pay here $272k

This role pays less than 55% of similar roles. Most pay $197,925–$249,753 — the shaded band above. At the midpoint, this role pays about $211k versus about $224k 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 800 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 795 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Lead Machine Learning Engineer (Manager IC)

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As a Lead Machine Learning Engineer at Capital One, you will join an Agile team focused on building and productionizing foundation models using self-supervised learning techniques for transformer architectures. Your role involves designing, developing, and implementing large-scale training systems that leverage Capital One’s extensive behavioral data to enhance applications in areas such as fraud detection, marketing, and customer service. You will be responsible for driving architectural decisions, reviewing code, and ensuring the high availability and performance of machine learning models in production environments. This position requires expertise in self-supervised learning, transformer modeling, and ML engineering best practices, along with proficiency in relevant programming languages and tools.

Skills

Python Transformer Self-Supervised_Learning ML_Engineering Agile CI/CD Docker Kubernetes AWS PostgreSQL Prometheus Grafana

What you'll do

Design and develop foundation models using self-supervised learning techniques.
Train transformer architectures on large-scale behavioral data for various applications.
Ensure high availability and performance of machine learning systems in production.
Drive architectural decisions and innovations in ML engineering best practices.
Develop and review model and application code to maintain quality standards.

What we're looking for

Experience in developing and productionizing foundation models at scale.
Proficiency in self-supervised learning and transformer architectures.
Expertise in machine learning engineering best practices and innovations.
Strong background in model architecture, training, and representation learning.
Ability to ensure high availability and performance of ML applications.
Extensive experience in detailed technical design and implementation.
Bachelor’s Degree or equivalent required.

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