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Helping companies find solutions to supercharge growth

AI Engineer, RL & Evals

Posted: 1 month ago
Job Location
Remote Work Policy

In office

Visa Sponsorship

Not Available

RelocationAllowed
Skills
Python
Distributed Systems
Backend Development
Data Pipelines
Reinforcement Learning
PyTorch
LLMs
Full-Stack Engineering
Evaluation Frameworks
Evaluation Systems
Reinforcement Learning Environments
Machine Learning Post-Training Systems

About the job

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.

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