Senior Engineering Manager, ML Platform

Location: San Francisco, California or Seattle, Washington

Employment Type: Full time, Hybrid

ABOUT THE TEAM

The Machine Learning team — internally known as "Potato Radius" — builds the training pipelines, feature infrastructure, and evaluation systems behind every score Sift returns, across more than 700 customers and a trillion-plus events a year. We are Sift's Data Science and ML Engineering team responsible to ship models fast, prove they work, and trust them in production.

WHAT WE'RE LOOKING FOR

We're hiring a Senior Engineering Manager to lead this team. You're a manager who's inspiring and technical, and who knows how to bring focus to what matters now without losing sight of the long term. You value collaboration and transparency, operate with a get-stuff-done mindset, and bring the technical depth and bias for shipping to spot the manual, brittle, or duplicated work that's quietly slowing the team down. You build a culture of mentorship, give regular and constructive feedback, set clear goals, and grow your team by hiring effectively.

PROJECTS YOU MIGHT LEAD

• Launch a unified model evaluation framework that gives Data Science fast, trustworthy, apples-to-apples comparisons before a model ever reaches production or shadow traffic.

• Evolve core feature infrastructure — including a new global feature store — to improve accuracy and unlock faster experimentation.

• Bring a fresh approach to model configuration, replacing tribal knowledge and manual gating with auditable, safely-controlled releases.

• Introduce agentic, AI-assisted tooling into customer investigations, automating repetitive data pulls and validation so analysts spend their time on judgment calls, not manual digging.

• Build automation that detects an active fraud attack, adjusts score calibration in real time, and cleanly reverts once it subsides.

WHAT YOU'LL DO

• Lead and grow the team: Own the roadmap, execution, and quality of the systems that trai...