AI Engineer, RL & Evals

Raydar•San Francisco, CA

1d•$175,000 - $275,000•Onsite

About The Position

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. 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.

Requirements

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.

Nice To Haves

Experience building evaluations for creative, generative, or otherwise non-verifiable domains.
Experience developing platforms or environments for agentic systems.

Responsibilities

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.