RL Environment Engineer: Shape Frontier Model Learning

Acceler8 Talent; San Francisco (CA); On-site; USD 225,000 - 275,000; Full time

Benefits offered by this job

Equity

Job summary

Acceler8 Talent is hiring a Software Engineer to design reinforcement-learning environments for frontier model labs. You will turn research objectives into scalable environments, tasks, reward signals, and evaluation rubrics that drive model learning and behavior.

You’ll work on RL environments across coding, finance, and enterprise workflows, building robust pipelines and experiments that reveal why models succeed or fail, with in-person collaboration in San Francisco.

Qualifications

• Experience applying RL to LLM post-training, agents, or sequential decision-making.
• Experience building environments, reward functions, evaluation tasks, or scoring systems.
• Familiarity with RLHF, RLVR, policy optimization, or preference-based learning.
• Ability to design controlled experiments and interpret noisy results.

Responsibilities

• Turn research objectives into scalable RL environments and experiments.
• Design and implement RL environments, reward signals, and evaluation rubrics.

Skills

RL in LLM post-training

Environments & rewards

RLHF/RLVR

Experiment design & analysis

Job description

Acceler8 Talent is hiring a Software Engineer to design reinforcement-learning environments for frontier model labs. You will turn research objectives into scalable environments, tasks, reward signals, and evaluation rubrics that drive model learning and behavior.

You’ll work on RL environments across coding, finance, and enterprise workflows, building robust pipelines and experiments that reveal why models succeed or fail, with in-person collaboration in San Francisco.