Full-stack Engineer 4, Machine Learning Experiences (MLX)

Capital One Financial

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Quick summary

Work type
On-site
Location
San Jose, CAMcLean, VACambridge, MARichmond, VASan Francisco, CA
Salary
$179,400–$204,700 / yr
Employment
Full-time
Posted
4 days ago
Freshness
Confirmed live today
Nearby
99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $203k
This role $192k
$174k $231k
below market most similar roles pay here above market

This role pays less than 70% of similar roles. Most pay $192,050–$214,000 — the blue band above. At the midpoint, this role pays about $192k versus about $203k 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 · Full-stack Engineer 4, Machine Learning Experiences (MLX)

Role Posting Log in to save

JOB TITLE: Full-stack Engineer 4 - Machine Learning Experiences (MLX) The Full-stack Engineer 4 - Machine Learning Experiences (MLX) leads a portfolio of diverse technology projects and a team of developers to create solutions meeting regulatory needs. This role involves building robust cloud-based solutions, defining service boundaries, and implementing targeted refactoring to reduce technical debt. You will collaborate with product managers to deliver experiences that drive financial empowerment. The position requires proficiency in Java, Scala, Python, Go, Node.js, JavaScript, and TypeScript, alongside experience with Open Source RDBMS, NoSQL databases, Docker, Kubernetes, and various AWS tools. You will provide technical leadership in an Agile environment, establishing standards for design and operational excellence. The work focuses on driving a major transformation by leveraging cutting-edge open source frameworks and emerging technologies to solve complex business problems.

What does a Full Stack Engineer earn in California?

Median $197500 from 70 postings across 20 companies.

See salary data

Skills

Java Scala Python Go Node.js JavaScript TypeScript Rust C# AWS GCP Azure Docker Kubernetes RDBMS NoSQL CI/CD Infrastructure as Code Git GitHub Bitbucket Observability

What you'll do

  • Lead a portfolio of diverse technology projects and a team of developers to create distributed microservices.
  • Deliver robust cloud-based solutions using AWS, Docker, and Kubernetes to drive customer experiences.
  • Provide technical leadership to Agile teams by setting standards for design, development, and operational excellence.
  • Partner with architects to define service boundaries, integration patterns, and reusable frameworks.
  • Identify areas for improvement by implementing targeted refactoring and reducing technical debt.
  • Influence long-term technology strategy through the evaluation of emerging tools and practices.
  • Mentor other members of the engineering community to drive professional development.

What we're looking for

  • Bachelor's Degree or higher in Computer Science or a related quantitative field.
  • At least 4 years of experience in software engineering.
  • At least 2 years of experience with public cloud platforms, cloud-based productivity tools, or virtualization technologies.
  • Master’s Degree in Computer Science or a related field (preferred).
  • 7+ years of experience coding with more than two of: Go, Java, JavaScript/TypeScript, Python, Rust, C#, or Scala (preferred).
  • 3+ years of experience with database and database management systems (preferred).
  • 4+ years of experience contributing to open source frameworks (preferred).
  • 3+ years of experience with CI/CD pipelines, infrastructure as code, and automated testing frameworks (preferred).

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