Head of Machine Learning
EarnIn is seeking an experienced Head of Machine Learning to lead and scale the company's ML efforts. This role involves defining the ML roadmap, leading multiple ML teams, and driving operational excellence in deploying models from research to production. The ideal candidate will have a strong background in ML engineering and a proven track record of deploying ML models at scale, particularly in fast-paced startup environments.
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 A19Z, 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.
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 models at scale, particularly in fast-paced startup environments. This leader should have a strong coding foundation, deep familiarity with production-grade ML engineering practices, and the ability to bridge theoretical concepts with practical implementation. While the role is primarily strategic and operational, it also requires a willingness to be hands-on and contribute code when needed to support the team and accelerate key initiatives.
Posted June 2, 2026