Machine Learning Engineer
Raydar
Machine Learning Engineer
Raydar
AI-powered recruiting agency for tech roles
Raydar · San Francisco, United States · Full-time · Posted 2026-10-28
Salary: USD 150,000–300,000
Workplace: on_site
About the company
Our client is a software company.
The role
Raydar is recruiting for this role on behalf of our client. Design and build realistic simulated work environments, scoring systems and evaluation tasks used to train and assess AI models. The work covers generating detailed synthetic workplace data, hardening graders against shortcuts, and turning real-world feedback into new test cases. Candidates with a background in model post-training or reinforcement learning are a strong fit for this early-career role.
What you'll do
- Build simulated environments with generated records, files and communications that behave like real workplaces.
- Design graders and scoring functions that resist exploitation by models.
- Create benchmarks whose rankings track real-world performance.
- Convert user feedback and corrections into evaluation tasks.
- Take over environment and benchmark work currently led by the founders.
What we're looking for
- 0 to 3 years of experience.
- A degree from a top-30 school.
- A background in post-training or reinforcement learning, from research or industry.
- A good sense of what makes a simulated environment rich, detailed and believable.
- The ability to spot how a model might game an environment or grader, and to fix it.
- Strong enthusiasm for using AI tools to work more effectively.
Compensation and benefits
- Base salary: USD 150,000 to 300,000 per year
- Equity
Location and work model
- San Francisco, CA, United States
- On-site
- Full-time
Powered by Workable
Raydar is an AI-powered talent acquisition firm that serves tech-focused organizations on a contingency basis, charging client companies only after a successful hire. It uses proprietary AI to identify a large pool of candidates and conducts a short 15-minute AI-driven interview (recorded and transcribed) before human recruiters review materials, provide interview prep, and assist with offers and negotiations. What sets it apart is the blend of automated sourcing and screening with hands-on human oversight and tailored client support. Its goal is to help organizations hire more efficiently by speeding up sourcing while maintaining thorough evaluation and negotiation assistance.
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