Director, Machine Learning Engineering

About the role

Chime's Data Science & Machine Learning team powers decisions across the company, from how we protect members to how we build products for them. We're looking for a Director to lead that team through its biggest shift yet: moving from traditional models to a modern, AI-driven approach built on transformers and foundation models. You'll lead managers and staff-level engineers, define what great ML looks like at Chime's scale, and rebuild the practice around it. If you want to shape the future of ML at a company where it directly affects members' financial lives, this is the role.

In this role, you can expect to

• Lead and grow Chime's ML organization, managing managers and staff-level engineers across all of Chime's ML work.

• Set the vision and roadmap for moving Chime's models from traditional approaches to transformer- and foundation-model-based systems.

• Coach your managers to build strong, high-performing teams, and raise the technical bar across the practice.

• Shape the architecture of Chime's ML platform, including how we train, fine-tune, serve and scale models on a modern GPU-based stack.

• Define what good ML looks like at Chime: standards for model development, evaluation, deployment and monitoring.

• Partner with product, engineering, risk and business leaders to turn ML into measurable impact for members.

• Make the call on when to build, buy or fine-tune, and explain the trade-offs clearly to executives.

To thrive in this role, you have

• Deep machine learning expertise, with a well-formed point of view on transformer and foundation models and where they do (and don't) beat traditional approaches.

• Familiarity with GPUs and the modern ML stack, from training and fine-tuning to serving models in production at scale.

• Experience managing managers and staff-level ICs, with the technical credibility to earn their trust.

• A track record of building or transforming an ML practice: hiring, setting standards and growing leaders.

• Experience setting a multi-year ML strategy and turning it into shipped results.

• Clear communication with executives and cross-functional partners; you can make complex ML trade-offs easy to follow.

• Bonus: experience applying ML in fintech or another regulated industry.

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Below is the base salary offered for this role and level of experience. Full-time employees may also be eligible