Software Engineer, Machine Learning Platform

Benefits

Parental leave

Not verified not verified - source URL not recorded; timestamp not recorded

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Offered From the posting source checked Jun 20, 2026
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

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Verification

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Salary

$187K-$259K From the posting source checked Jun 20, 2026

401(k) match

Reported not verified - source not recorded; source URL not recorded; timestamp not recorded

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

91% above the BLS role benchmark for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

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Company

Equity

Offered From the posting source checked Jun 20, 2026

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Software Engineer, Machine Learning Platform San Francisco, CA, USA 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

Read the full description at boards.greenhouse.io. FewerJobs shows a preview and links to the original posting.