Head of Machine Learning, India

EarnIn
Bengaluru, IndiaPosted 27 March 2026

Job Description

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 EarnIn is a fintech company where machine learning is embedded across our platform capabilities to power business decisions and customer experiences at scale. From risk and fraud to growth, personalization, and operational efficiency, ML systems are mission‑critical to our success. Ensuring the reliability, performance, and scalability of these systems in production is therefore a core engineering priority. The Head of Machine Learning, India, will be responsible for the success of ML systems built and operated by our India teams. This role sits at the intersection of applied science and engineering excellence, with a strong emphasis on translating research and experimentation into robust, high‑performance production systems. The ideal candidate has deep, hands-on experience deploying ML at scale, thrives in fast‑growing environments, and brings both theoretical grounding and strong production-engineering instincts. As EarnIn continues to expand in India, this role will inherit a high‑performing machine learning team, with clear potential to grow and scale the organization over time. As the senior ML leader in‑country, the role may also include site leadership responsibilities and close collaboration with HR and Talent Acquisition on hiring, culture building, and team engagement. This position will be hybrid from our Bengaluru office, as part of our expanding site, with 2+ days in the office. EarnIn provides excellent employee benefits, including healthcare, internet/cell phone reimbursement, a learning and development stipend, and opportunities to collaborate with and travel to our Mountain View HQ and Bangkok Site. Our salary ranges are determined by role, level, and location. WHAT YOU'LL DO Build, manage, and mentor a high‑performing team of machine learning engineers; foster collaboration, support career growth, and invest in continuous skills development. Own the delivery and impact of ML initiatives, working closely with cross‑functional partners to ensure measurable business outcomes. Lead the design, development, and optimization of ML‑based systems, including techniques such as deep learning and reinforcement learning. Drive a culture of scientific and engineering rigor balanced with real‑world pragmatism, with a strong focus on experimentation, evaluation, and quantifying impact on key engagement and business metrics. Partner with data engineering, product management, and marketing teams to take ML solutions from conception through experimentation to reliable, timely production deployment. Establish India as a strategic ML hub for EarnIn by leading hiring efforts, onboarding, and close partnership with HR and TA on culture building, team health, and local engagement initiatives. WHAT WE'RE LOOKING FOR MS or Ph.D. in Computer Science, Statistics, or a closely related technical field. 7+ years of industry experience, including 3+ years of people management experience. Strong depth across core machine learning algorithms and applied ML techniques. Proven experience building, deploying, and operating production ML systems at scale. Advanced proficiency in Python and SQL, with a strong software engineering foundation. Excellent written and verbal communicati ... (truncated, view full listing at source)
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