Staff ML Engineer - RL for LLMs & Generalization

Cohere; United States; Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Remote-friendly

Job summary

Cohere is seeking a senior RL researcher in the United States to design, run, and analyze large-scale RL post-training experiments for LLMs, including RLHF.

You will explore out-of-distribution generalization, reward design, and task diversity, and build held-out evaluations to catch reward hacking and benchmark overfitting. This role is remote-friendly with offices worldwide, fostering a global research team.

Qualifications

• Hands-on LLM training experience required.
• Experience applying RL to LLMs (PPO, GRPO, RLHF).
• Strong research and software engineering skills.
• Excellent communication and data quality intuition.

Responsibilities

• Design, run, and analyze large-scale RL post-training experiments.
• Research methods for out-of-distribution generalization and reward design.
• Build held-out evaluations to detect reward hacking and overfitting.

Skills

LLM training experience

Reinforcement learning

Experimentation rigor

Software engineering

Communication skills

Tools

PPO

RLHF

GRPO

Job description

Cohere is seeking a senior RL researcher in the United States to design, run, and analyze large-scale RL post-training experiments for LLMs, including RLHF.

You will explore out-of-distribution generalization, reward design, and task diversity, and build held-out evaluations to catch reward hacking and benchmark overfitting. This role is remote-friendly with offices worldwide, fostering a global research team.