Senior Machine Learning Engineer

About the company

Our client is a cybersecurity company.

The role

Raydar is recruiting for this role on behalf of our client. Own the design, training and production deployment of machine learning systems behind a core detection capability. Partner closely with technical leadership and help set engineering standards on a small, fast-moving team.

What you'll do

• Design and build machine learning models that flag suspicious activity as it happens.
• Take models from research into production and measure how they behave at scale in a live environment.
• Architect systems that can absorb significant growth in data volume and traffic.
• Talk with customers to understand the threats they face and uncover new signals that strengthen detection.
• Set technical patterns, push for correctness and raise the quality bar across the team.
• Own systems end to end, from data pipelines through serving and infrastructure.

Requirements

What we're looking for

• 4+ years of machine learning engineering experience, including shipping models to production at scale.
• A solid mathematical grounding, including statistics, linear algebra and applied modeling of anomalous behavior.
• Experience training and deploying models, with good judgment about which approach fits a problem and where its limits lie.
• Strong engineering fundamentals, including clean production-grade Python and end-to-end system ownership.
• Hands-on background with low-latency data processing and scalable storage and compute systems.
• High agency: you scope your own work, propose solutions and execute without direction.
• Fast learner who ships quickly and is comfortable in a small, high-autonomy team.
• Pride in craft and in building things that hold up over time.

Bonus points

• Background in high-stakes domains such as quantitative finance or fraud detection.
• Experience shipping production machine learning at an early-stage company or on an ML infrastructure team.
• Degree in computer science, math or a quantitative field.
• First-author publication at a leading machine learning conference.

Benefits

Compensation and benefits

• Base salary: USD 250,000 to 300,000 per year
• Equity
• Health, dental and vision coverage
• Retirement plan
• Commission

Location and work model

• San Francisco, CA, United States
• On-site, 5 days per week in office
• Full-time