Director, Machine Learning Engineering
Chime · San Francisco, CA, USA
About this role
**Director, Machine Learning Engineering — Chime** ## 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 the team through its biggest shift yet: moving from traditional ML models to a modern, **AI-driven approach using 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. ## What you’ll do - Lead and grow Chime’s ML organization, managing managers and staff-level engineers across all ML work. - Set the vision and roadmap to move Chime’s models from traditional approaches to **transformer- and foundation-model-based systems**. - Coach 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 standards for model development, evaluation, deployment, and monitoring. - Partner with product, engineering, risk, and business leaders to deliver measurable impact for members. - Decide when to **build, buy, or fine-tune**, and clearly explain trade-offs to executives. ## What you bring - Deep machine learning expertise, with a strong point of view on **transformers and foundation models** (and when they do—and don’t—outperform traditional approaches). - Familiarity with GPUs and the modern ML stack, from training/fine-tuning to production serving at scale. - Experience managing managers and staff-level ICs, with the technical credibility to earn trust. - Track record of building or transforming an ML practice (hiring, setting standards, growing leaders). - Experience setting a multi-year ML strategy and turning it into shipped results. - Clear communication with executives and cross-functional partners; able to make complex ML trade-offs easy to follow. - **Bonus:** experience applying ML in fintech or another regulated industry. ## Location / Work style - **#LI-Onsite** (in-office policy: four days/week in office; Fridays from home for those near an office) ## Compensation (base salary range) - **$269,000 – $373,000 USD** *Full-time employees may also be eligible for bonus(es), competitive equity, and benefits.*
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