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
Skills Required
- 4+ years of machine learning engineering experience
- Experience shipping machine learning models to production at scale
- Strong mathematical grounding in statistics, linear algebra, and applied modeling of anomalous behavior
- Experience training and deploying machine learning models
- Strong engineering fundamentals, including clean production-grade Python
- End-to-end system ownership
- Hands-on experience with low-latency data processing and scalable storage and compute systems
- Ability to scope work independently, propose solutions, and execute without direction
- Ability to learn quickly and work in a small, high-autonomy team
- Background in 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, mathematics, or a quantitative field
- First-author publication at a leading machine learning conference
What We Do
Raydar is a talent acquisition and business consulting firm that connects world-class and emerging talent with growing organizations. It supports companies through team development, strategic hiring, and customized growth solutions, helping clients recruit roles such as engineers, product managers, executives, legal counsel, and quantitative traders. Raydar focuses on understanding each organization’s needs, culture, and long-term goals to build high-impact teams.
