Raydar Jobs

Machine Learning Engineer

Raydar

Machine Learning Engineer

Posted 19 Hours Ago

In-Office

San Francisco, CA, USA

150K-300K Annually

Entry level

In-Office

San Francisco, CA, USA

150K-300K Annually

Entry level

Design and build realistic simulated workplace environments, evaluation tasks, benchmarks, graders, and scoring systems for training and assessing AI models. Generate synthetic records, files, and communications; prevent models from exploiting evaluation systems; align benchmarks with real-world performance; and convert user feedback into new test cases. The role is early-career and emphasizes reinforcement learning or model post-training experience.

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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.

Requirements

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.

Benefits

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

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