Machine Learning Engineer, LLM Post-Training

About the Role

We are looking for a hands-on Machine Learning Engineer to drive the post-training of our large language models, with a strong emphasis on reinforcement learning (RL). You will own the full post-training stack continuous pre-training (CPT), supervised fine-tuning (SFT), and RL along with the data preparation that powers it. Just as important, you will work directly with product and business teams to translate real-world use cases into concrete training objectives and ship model improvements quickly. This is a high-ownership role for someone who has actually trained models, not just read about it.

Responsibilities

• Lead post-training of our LLMs across the full pipeline: continuous pre-training, SFT, and reinforcement learning, with RL as the primary focus (e.g., RLHF, PPO, GRPO, DPO, and related methods).
• Design, build, and curate the data that drives each training stage instruction/SFT datasets, preference pairs, reward signals, on-policy rollouts, and rejection-sampled completions and define target="_blank">CPRA Privacy Notice for California Candidates