Senior Applied Researcher, Member of Technical Staff

About the Role

Join a small applied research team working directly with advanced AI research organizations on challenging model post-training problems. This research-first role focuses on reinforcement learning, training data quality, and experiments that lead to measurable improvements in model capabilities.

What You'll Do

• Partner with research teams to turn open-ended goals into concrete environments, datasets, experiments, and deliverables.

• Design and run post-training workflows using reinforcement learning methods such as GRPO, preference optimization, and supervised fine-tuning.

• Shape and inspect high-quality trajectories and training data, paying close attention to correctness, edge cases, and quality.

• Develop reward functions, rubrics, validators, and evaluation harnesses that resist reward hacking and measure real capability gains.

• Analyze post-training signals and experiment results across distributed GPU clusters to guide next steps.

What We're Looking For

• At least 2 years of experience as an applied researcher, research scientist, or in a comparable research role.

• Hands-on model training experience in an advanced AI research lab, a newer AI lab, or an AI data organization, or research publications or released models with strong benchmark results.

• Practical reinforcement learning and agent experience beyond typical machine learning engineering work.

• Strong experience with Python, PyTorch, FSDP, FastAPI, GRPO, and distributed GPU clusters.

• Research depth in reinforcement learning and training data; a PhD involving RL research is relevant.

Compensation & Benefits

Base salary is $300,000 to $500,000 annually. Visa sponsorship is available.

Location

Hybrid role based primarily in New York, New York.