AI Engineer, RL & Evals
Raydar
- Location
- Onsite (San Francisco, California)
- Compensation
- $175k - $275k/yr
- Employment
- Full-time
- Level
- Mid Level
About the Role
Raydar is a seed-stage AI company building infrastructure to improve how models handle subjective creative work. This role involves designing reinforcement learning environments and evaluation frameworks for design domains while shipping production backend systems.
Skills
Perks
- Competitive equity
Full job details
About the company
Our client is a seed-stage AI company building the data and infrastructure layer to improve how AI models handle subjective work. Its initial focus is design, where it develops reinforcement learning environments and evaluation systems for creative output. The team works with frontier AI labs and application companies on training, evaluation, and product infrastructure.
The role / why it matters
As an AI Engineer focused on reinforcement learning and evaluations, you will build the systems that help models improve on tasks where there is no single objectively correct answer. This is a production engineering role at the intersection of backend development and applied machine learning, with ownership from environment design through shipped infrastructure.
What you'll do
- Build and scale reinforcement learning environments and evaluation frameworks for creative domains such as design.
- Design tasks and grading rubrics that measure quality in subjective domains.
- Develop agent harnesses and context layers for API and product infrastructure.
- Work with research teams to create environments that improve AI model output.
- Ship production software end to end, including backend systems and data pipelines.
What we're looking for
- At least two years of relevant engineering or applied machine learning experience.
- Experience building reinforcement learning environments, evaluation systems, or machine learning post-training systems.
- Strong backend or full-stack engineering experience shipping production products.
- Practical skills in Python and PyTorch, with working knowledge of reinforcement learning, LLMs, evaluation frameworks, and distributed systems.
- A computer science degree.
- Ability to collaborate across engineering and research and communicate fluently in English.
Bonus points
- Experience building evaluations for creative, generative, or otherwise non-verifiable domains.
- Experience developing platforms or environments for agentic systems.
Compensation and benefits
The base salary range is $175,000 to $275,000 USD, plus competitive equity.
Location / work model
This is a full-time, on-site role in San Francisco, five days per week.