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Signifyd is hiring a Senior Machine Learning Engineering Manager to lead one of the teams within Signifyd AI Lab (SAIL), the department responsible for building ML products that power fraud and risk decisions across billions of e-commerce transactions annually.
In this role, you will lead and grow a team of ML engineers in a hands-on, player-coach capacity. You'll balance technical credibility with leadership rigor—staying close enough to the work to evaluate code quality, inspection pipelines, and statistical validity, while also mentoring engineers, managing career development, and translating complex ML metrics into business outcomes for Risk leadership.
Key responsibilities include:
**Team Leadership & Development**: Guide career development, conduct 1:1s, provide constant feedback, and create a psychologically safe environment where negative experimental results are celebrated as progress. Conduct technical interviews, train the team on hiring practices, and help raise the bar as the organization scales.
**Portfolio Management**: Partner with tech leads who own the technical roadmap. Your role is to pressure-test ideas, sharpen them, allocate compute and headcount to the strongest hypotheses, and make clear calls on which bets get resourced, iterated, or documented as "no." You'll manage the trade-off between committed improvement targets and longer-horizon research bets, re-cutting budgets as evidence arrives.
**Rigor & Validation**: Bring statistical rigor to how the team validates results. You'll ensure offline improvements predict online behavior, evaluate whether gains survive rolling evaluations, and determine whether improvements are already captured by prior changes. You'll own delivery cadence and ensure well-documented negative results are treated as real outcomes.
The environment is one of experimentation and ambiguity—the roadmap is a set of hypotheses, and you thrive in settings where the answer to "will this work?" is "we'll know in three weeks." You balance research velocity against quarterly delivery, disagree and commit when decisions are made, and foster a culture where those closest to problems are empowered to solve them.
This is a fully remote role based in the US, ideal for someone with deep ML engineering experience, proven people management skills, and the judgment to lead high-impact technical teams in a fast-moving fintech/fraud-prevention environment.
