Early-stage AI cybersecurity team protecting Microsoft 365 from identity-driven attacks
Senior Machine Learning Engineer
You'll spend mornings reviewing model drift on detection pipelines that catch forged invoices and stolen credentials, then afternoons shipping improvements to production. The work sits at the intersection of adversarial ML and enterprise SaaS: training classifiers on behavioral signals, building feedback loops from analyst triage, and hardening models against attackers who adapt fast. Expect to pair with infrastructure engineers on latency budgets measured in milliseconds, and to present precision-recall tradeoffs to the security operations team.
What they're looking for
- 4+ years shipping production ML systems, with recent depth in classification or anomaly detection at scale
- Proficiency in Python and at least one of NodeJS or TypeScript; comfort reading React frontends for debugging
- Demonstrated experience with adversarial domains—security, fraud, abuse, or similar cat-and-mouse problems
- Strong opinions on observability for ML: drift detection, shadow deployments, and explainability under regulator scrutiny
- Willingness to work on-site in San Francisco with a tight-knit team of fifteen