Head of Machine Learning
Earnin - Mountain View, US
Posted Jul 25, 2025
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
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- Salary
- Not verified not verified - source not recorded; timestamp not recorded
- 401(k) match
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Schedule
- Shift type
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Head of Machine Learning Mountain View, US About EarnIn As one of the first pioneers of earned wage access, our passion at EarnIn is building products that deliver real-time financial flexibility for those with the unique needs of living paycheck to paycheck. Our community members access their earnings as they earn them, with options to spend, save, and grow their money without mandatory fees, interest rates, or credit checks. We're fortunate to have an incredibly experienced leadership team, combined with world-class funding partners like A16Z, Matrix Partners, DST, Ribbit Capital, and a very healthy core business with a tremendous runway. We're growing fast and are excited to continue bringing world-class talent onboard to help shape the next chapter of our growth journey. POSITION SUMMARY We are seeking an experienced and visionary Head of Machine Learning to lead and scale our machine learning efforts across the company. As a fintech company where data and machine learning (ML) is integral to both our business strategy and user experience, we depend on robust, scalable systems to drive impactful decisions and deliver exceptional customer value. Our mission is to pioneer success stories through the application of generative AI and state-of-the-art machine learning algorithms, thereby generating transformative business and societal impact. The Head of ML will drive operational excellence across our machine learning systems by defining and executing a vision that moves models from research to production with strong performance, reliability, and maintainability. The ideal candidate will bring a proven track record of deploying ML
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