Head of Applied Machine Learning (ML)

SentiLink stops more than 150,000 fraud attempts and verifies more than 3 million identities every day to protect both institutions and consumers. The problems we work on are challenging, and solving them takes deep domain expertise, rigorous analysis, and a willingness to dig into the details. At SentiLink, you'll work alongside smart, highly collaborative colleagues who respect each other's time and judgment, take ownership, and follow through on their commitments. Together, we do truly meaningful work protecting the identities of innocent consumers and flagging the fraudsters attempting to exploit them. We're well capitalized and growing quickly. We already serve 13 of the top 15 U.S. banks, we're expanding into new markets, and we're backed by Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin. We've been named to the Forbes Fintech 50 and as a 2026 FICO Industry Vanguard Decision Award Winner . We were also the first company to go live with the electronic Consent Based Social Security Number Verification (eCBSV) service, and we've testified before the U.S. Congress on the future of identity. We want SentiLink to be the best place you've ever worked. We offer generous benefits and support a range of working arrangements, from fully remote to in-office. We are a digital-first company with strong collaboration across the U.S. and India, and we meet in person regularly to build relationships. We have offices in Austin, San Francisco, New York City, Seattle (Bellevue), Los Angeles, and Chicago in the U.S., and in Gurugram (Delhi) and Bengaluru in India.

SentiLink builds the fraud detection and identity verification models much of the US financial system runs on. As Head of Applied ML, you own a major ML domain end to end. You'll lead a team of 4 applied ML scientists, 6 by the end of 2026, all experienced and technically deep enough to challenge you daily. This is a people management role that stays close to the work. Technical credibility is non-negotiable: you'll review PRs, push on modeling decisions, and unblock the team. Data science drives product decisions here, and we expect you to become a strategic leader in both the product and ML domains you own. We use AI across all of our work, are exploring where it belongs in the products themselves, and hold a hard line on AI safety and data governance. Technologies: Python 3, PostgreSQL, AWS, XGBoost, scikit-learn, pandas, Elasticsearch and OpenSearch, Neo4j, MLflow, Flyte, and use of modern LLM tooling.

Directly manage a team of applied ML scientists, 4 today and growing to 6 by the end of 2026, and set the engineering and modeling practices they work by. Own strategy and execution for your applied ML domain: roadmap, priorities, resourcing, and results. Act as a technical mentor who can dive deep and give specific, useful direction. Guide modeling and architecture decisions, review PRs, and stay current on the codebase and production systems. Partner with senior leadership, Product, Engineering, and Risk to set priorities and deliver on aggressive timelines. Represent your domain in product strategy discussions and help shape where those products go next. Own SentiLink's fraud detection and identity models across the full lifecycle: data acquisition, feature engineering, labeling strategy, model training, experimentation, production deployment, monitoring, and iteration. Research emerging fraud patterns, build new ML capabilities for identity verification and financial risk, and design analyses that inform product and business decisions. Drive how the team uses AI in its own work, keep pushing the boundary on what that unlocks, and help define where AI belongs in our products.

10+ years of industry experience applying machine learning or statistics to real-world problems, or 7+ years with a relevant PhD, including 6+ years directly managing machine learning or data science teams across two companies or more. Startup experience