Member of Technical Staff - Post-training (Data Infrastructure)

Job summary

Responsibilities

As a Member of Technical Staff in Post-Training Data Infrastructure, you will build and own the pipelines that produce the post-training data for our large language models (LLMs), from SFT and RL data to synthetic and human-annotated data.

• Build and maintain data pipelines for SFT, preference, and RL post-training data.
• Own dataset quality, versioning, and reproducibility.
• Turn research data recipes into production-grade, reusable components.
• Scale model inference for data generation and model-based grading.
• Design data formats and schemas that keep post-training datasets consistent and efficient to train on.

What they're looking for

• Strong software engineering skills.
• Experience designing and building large-scale data pipelines for machine learning, ideally for LLM post-training.
• Track record of running distributed data processing and model inference at scale.
• Good understanding of post-training methods (e.g., SFT, RLHF, DPO) and how data shapes model behaviour.
• Excellent communication skills.