Member of Technical Staff - Post-Training (Reinforcement Learning & Generalization)

Cohere

3d•$175,000 - $380,000•Remote

About The Position

As a Member of Technical Staff in Post-Training, you will train large language models (LLMs) with reinforcement learning and develop methods that help them generalize beyond the distribution they were trained on. You will design the training recipes, environments, and evaluations that determine if a model has truly learned a skill or has only fitted its training tasks, and turn what works into the recipes behind production models. You will work closely with the post-training data infrastructure, evaluation, and pre-training teams.

Requirements

Strong research and software engineering skills, with hands-on experience training LLMs.
Experience applying reinforcement learning to LLMs (e.g., PPO, GRPO, RLHF, RLVR), ideally at scale.
Track record of work on generalization, robustness, or distribution shift, through publications or shipped models.
Rigorous experimental practice: clean ablations, careful controls, and sound conclusions from noisy results.
Excellent communication skills.
Deep understanding of data quality principles and best practices: demonstrates willingness to dive deep into data while possessing strong intuition for assessing the quality of datasets and anticipating how different data characteristics will impact model training outcomes.

Nice To Haves

Experience with distributed training (e.g., JAX, PyTorch, FSDP, Megatron) is a plus.

Responsibilities

Design, run, and analyse large-scale RL post-training experiments (e.g., RLHF, RL from verifiable rewards).
Research and develop methods that improve out-of-distribution generalization, such as reward design, environment and task diversity, curricula, and regularization.
Build held-out evaluations that measure generalization to unseen tasks, domains, and formats, and that catch reward hacking and benchmark overfitting.
Diagnose training dynamics and failure modes, including instability, reward over-optimization, and capability regressions.
Turn successful research into robust, reproducible training recipes for production models.

Benefits

A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch.
Full health and dental benefits, including a separate budget for mental health.
RRSP matching, 401K, Pension Scheme.
100% Parental Leave top-up for up to 6 months, for either parent.
Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit.
Education & learning stipend for conferences, courses, and coaching.
6 weeks of paid vacation (30 working days!)
Budget for traveling to other offices if you are remote, plus an annual company offsite.
A daily lunch program, plenty of snacks, and regular community and social events (for those in the office).
A co-working benefit so you can work alongside others in your city (for those not near an office).
$500 home office stipend to set up your workspace properly.