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Senior Machine Learning Engineer

Raydar · San Francisco, CA, United States · Onsite

  • Professional Services
  • 11–50 employees
  • Santa Monica, California

Strong hiring record · median 33 days open

100100

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Senior Machine Learning Engineer at Raydar. We’ll keep it in your applied jobs, so you can see it later and be warned before applying to the same employer twice.

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

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