JOB-1588
A fast-growing cybersecurity startup that detects hijacked user accounts as they happen is adding machine learning engineers to its small technical team. You would take responsibility for the core detection models, staying close to customers and the real attackers they face.
Your focus
- Design and evolve the models that spot account takeover in real time, working alongside technical leadership
- Carry models from experimentation into a live system and measure how they behave against real adversaries at scale
- Architect solutions that can absorb a tenfold or greater jump in volume without a rewrite
- Speak with customers about the threats they see and use that insight to hunt for new signals
- Serve as an experienced technical influence who sets patterns and lifts quality on a lean team
Ideal background
- Four or more years in ML engineering, with substantial experience putting models into live production
- Solid quantitative base: statistics, anomaly detection, linear algebra, NLP and behavioral modeling
- Good judgment on model choice, including a clear view of each approach’s weaknesses
- Clean production-quality code and willingness to own a system beyond the modeling layer
- Exposure to streaming data, feature stores, high-performance databases or distributed systems; fraud or quantitative finance is a plus
- Self-directed, fast-moving and comfortable with high autonomy
- Stack today: Node, TypeScript, React and Python
On-site in the San Francisco Bay Area. Applicants must already be authorized to work in the US; visa sponsorship and transfers are not available.
