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Software Engineer, Machine Learning Platform

Chime

San Francisco, USonsite$187k-$259k/yrPosted May 15, 2026

At a glance

Highlights

  • Four days office, Friday remote
  • Competitive salary and equity
  • FinTech scale impact

Heads up

  • On-call rotations required
  • Four days in-office requirement

Why this role might suit you

The role offers senior engineers a chance to shape a large‑scale ML platform at a fast‑growing fintech, combining cloud infrastructure, distributed training, and real‑time inference while enjoying competitive compensation and a supportive in‑office culture.

Skills

pythongoscalajavaawsterraformraykinesiskafkaflinksparkdockerkubernetescudacloudformationci-cdobservability

About the role

About the role

Chime’s Machine Learning Platform (MLP) team builds and operates the infrastructure, tooling, and developer experience that powers machine learning across the company. We enable data scientists and ML engineers to develop, train, deploy, and monitor models reliably and efficiently.

As a Machine Learning Platform Engineer, you will design and build scalable systems that support model training, feature computation, real-time inference, and experimentation. You’ll work at the intersection of distributed systems, cloud infrastructure, and applied machine learning.

This role focuses on building robust foundations that allow ML teams to move quickly while maintaining reliability, governance, and cost efficiency.

The base salary offered for this role and level of experience will begin at $187,000.00 and goes up to $259,000.00. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.

In this role, you can expect to

Design, build, and operate scalable ML infrastructure on AWS

Develop distributed training and batch processing systems using Ray

Build and maintain infrastructure-as-code using Terraform

Support and evolve the feature store and feature pipelines

Develop data ingestion and streaming systems (e.g., Kinesis, Kafka, Flink, Spark, or similar technologies)

Improve CI/CD workflows for ML models and platform components

Enhance observability, reliability, and cost visibility across ML workloads

Partner closely with Data Science and ML Engineering teams to improve developer experience

Contribute to platform architecture decisions and technical roadmaps

Participate in on-call rotations to support production systems

To thrive in this role, you have

5+ years of experience in ML infrastructure, platform engineering, or production ML systems

Knowledge of the machine learning model development lifecycle, including data preprocessing, model training, evaluation, and deployment

Experience with distributed systems, cloud computing, or large-scale data processing

Strong foundation in computer science and software engineering principles

Deeply interested in the impact and evolution of advanced AI technologies

Hands-on experience with CI/CD pipelines, DevOps practices, and infrastructure as code

Experience with containerization technologies such as Docker and Kubernetes, and orchestration systems

Knowledge of cloud platforms such as AWS and distributed computing frameworks such as Spark and Ray

Experience with GPU programming(CUDA) and GPU costs/optimization

Strong programming skills in Python, Go, Scala, Java or similar languages

Familiarity with infrastructure-as-code (e.g., Terraform, CloudFormation)

Solid understanding of software engineering fundamentals (testing, version control, code review, observability)

Nice-to-have

Experience with distributed compute frameworks such as Ray

Experience building or operating a feature store

Experience with real-time ML systems or model serving

Familiarity with streaming technologies (Kafka, Kinesis, Flink, Spark Streaming, etc.)

Experience supporting ML lifecycle workflows (training, evaluation, deployment, monitoring)

Knowledge of ML experimentation platforms and model governance practices

#LI-GC1 #LI-SF

A little about us

At Chime, we believe that everyone can achieve financial progress. We created Chime—a financial technology company, not a bank—on the premise that core banking services should be helpful, easy, and free. Through our user-friendly tools and intuitive platforms, we empower our members to take control of their finances and work towards their goals. Whether it's starting a savings account, purchasing a first car or home, launching a business, or pursuing higher education, we're proud to have helped millions unlock their financial potential.

We're a team of problem solvers, dreamers, and builders with one shared obsession: our members. From day one, Chimers have worked tirelessly to out-hustle and out-execute competitors to bring our mission to life. Their grit and determination inspire us to work harder every day to deliver the very best experience possible. We each bring an owner's mindset to our work, refusing to be outdone and holding ourselves accountable to meet and exceed the highest bars for our teams, our company, and our members.

We believe in being bold, dreaming big, and taking risks, while also working together, embracing our diverse perspectives, and giving each other honest feedback. Our culture remains deeply entrepreneurial, encouraging every Chimer to see themselves as stewards of our mission to help everyday Americans unlock their financial progress.

We know that to achieve our mission, we must earn and keep people's trust—so we hold ourselves to the highest standards of integrity in everything we do. These aren't just words on a wall—our values are embedded in every aspect of our business, serving as a north star that guides us as we work to help millions achieve their financial potential.

Because if we don't—who will?

Chime is a financial technology company, not a bank. Banking services provided by The Bancorp Bank, N.A. or Stride Bank, N.A., Members FDIC.

What we offer for our full-time, regular employees

🏢 Our in-office work policy is designed to keep you connected - with four days a week in the office and Fridays from home for those near one of our offices, plus team and company-wide events depending on location. Whether you’re coming in regularly or are part of our fully remote program, you’ll stay engaged with your work and teammates.

💻 In-office perks including backup child, elder, and/or pet care, plus a subsidized commuter benefit to support your regular commute

💰 Competitive salary based on experience

✨ 401k match plus great medical, dental, vision, life, and disability benefits

🏝 Generous vacation policy and company-wide Chime Days, bonus company-wide paid days off

🫂 1% of your time off to support local community organizations of your choice

👟 Annual wellness stipend to use towards eligible wellness related expenses

👶 Up to 24 weeks of paid parental leave for birthing parents and 12 weeks of paid parental leave for non-birthing parents

👪 Access to Maven, a family planning tool, with $15k lifetime reimbursement for egg freezing, fertility treatments, adoption, and more.

🎉 In-person and virtual events to connect with your fellow Chimers—think cooking classes, guided meditations, music festivals, mixology classes, paint nights, etc., and delicious snack boxes, too!

💚 A challenging and fulfilling opportunity to join one of the most experienced teams in FinTech and help millions unlock financial progress

We know that great work can’t be done without a diverse team and inclusive environment. That’s why we specifically look for individuals of varying strengths, skills, backgrounds, and ideas to join our team. We believe this gives us a competitive advantage to better serve our members and helps us all grow as Chimers and individuals.

To learn more about how Chime collects and uses your personal information during the application process, please see the Chime Applicant Privacy Notice.

Compensation

This Machine Learning Engineer role pays $187k-$259k/yr. Within typical range for machine learning engineer roles in United States.

Questions about this role

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