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