Founding Post-Training Researcher Inference research

Be our first dedicated post-training hire. You’ll own the loop that turns customers’ production traces into smaller, cheaper open models built for their workloads.

Our automated RL product, Gradiated Training, is in private beta. It takes a team’s production traces, builds evals around their tasks, and post-trains an open model for that workload. In one early case, SFT followed by GRPO took GLM-5.3 Flash from 54% to 76% on a support agent task, at about 1/25th the cost of a frontier model.

The loop is starting to work, but it’s early. You’ll be our first dedicated post-training hire. You’ll own and improve the loop that takes production trace data and turns that into cost effective LoRA adapters.

• The pipeline, end to end: take raw production traces all the way to a model we’re confident putting into production
• Recipes that generalize:
  Test SFT, GRPO and new training methods across real customer environments. This will be hands on, working with customer data to see what works, and then trying to generalize it
• Building an RL environment pipeline:
  We are using customers trace data and github repositories to reconstruct RL environments. This has a lot of variation in practice, so working directly with customer data to trial this on many different environments is important.
• Honest evals: judge models, rubrics and baselines that tell a customer what got better and what got worse
• The team: help hire and shape post-training as it grows, and share what we learn publicly

• Several years post-training large language models that shipped to real users, for example at Deep Mind or a frontier lab. You owned the outcome, not just the experiments
• Hands-on experience running RL for LLMs (RLHF, PPO, GRPO, DPO or similar), and you have experience of how things break
• Experience building good evals
• You've built infrastructure for post-training, and run training jobs at scale in production
• You have experience leading a team focused on post-training
• Low ego. You write clearly, you ship, and you’d rather fix the thing than present about fixing it
• Based in London or Cambridge. We’re in person in Cambridge on Monday, Wednesday and Friday