Member of Technical Staff — RL Research (New PhD Grad)

Tech Stack

Responsibilities

• Build Nuance's RL/post-training stack from 0→1, covering rollout generation, policy optimization, reward/reference model serving, data feedback loops, evaluation, checkpointing, observability, and debugging.
• Develop and scale post-training methods such as PPO, GRPO, DPO, rejection sampling, RLHF/RLAIF, online RL, and model-based data improvement.
• Design systems abstractions to connect research ideas to production-scale RL runs, including trainers, rollout workers, reward models, evaluators, data queues, experience buffers, and checkpoint promotion.
• Build evaluation and feedback loops for omni behavior, focusing on turn-taking, interruption, timing, emotional response, audiovisual coherence, instruction following, and real-time interaction quality.
• Optimize the end-to-end post-training loop across various metrics like rollout throughput, serving latency, GPU utilization, policy update efficiency, and research iteration speed.

Benefits

• 401k
• Equity

Culture

Requirements