AI/ML Engineer

Benefits

Parental leave

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Market context

Median wage (BLS OEWS)

$111,944 national median

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

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

Schedule

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Weekend work

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Application

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About this role

AI/ML Engineer San Francisco, CA, USA About the role Chime's AI/ML Trust & Safety team is building models, insights, and decisioning systems that help protect millions of members while enabling safe, reliable financial progress. We are looking for an AI/ML Engineer who is growing strong technical depth in machine learning, experimentation, and analytical problem solving, with an interest in applying those skills to trust, safety, and risk challenges across Chime. You'll contribute to end-to-end model development, analysis, and production-facing decision systems with guidance from senior team members. Your work will help improve how Chime detects risk, understands member behavior, evaluates tradeoffs, and scales trustworthy member experiences. This role is a strong opportunity to build deeper expertise in applied ML, risk systems, experimentation, generative AI, sequence models, and cross-functional product impact in a high-scale environment. The base salary offered for this role and level of experience will begin at$125,000.00 and up to $173,000.00. 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 - Contribute to the design and implementation of training pipeline components for AI/ML models that support Chime's risk decisioning systems. - Develop, test, and iterate on model features within clear requirements and with support from senior team members. - Support offline model evaluation and contribute to online experiment analysis to understand performance, tradeoffs, and member impact. - Write modular, testable, and maintainable

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