Member of Technical Staff, Applied Researcher

About the Role

Join a small applied research team working directly with frontier AI research labs on challenging post-training problems. This research-first role focuses on improving model capabilities through reinforcement learning, high-quality training data, and carefully designed experiments.

What You'll Do

• Work with customer 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-fidelity trajectories and training data, with attention to correctness, edge cases, and quality.

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

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

What We're Looking For

• At least 2 years of experience as an applied researcher or research scientist.

• Hands-on model training experience in a frontier AI lab, newer AI research organization, or AI data lab, or published research or a released model with strong results on a notable benchmark.

• Demonstrated reinforcement learning experience; this role is research-focused and is not suited to an engineering background without RL work.

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

• Additional relevant background may include work at a frontier AI lab or a PhD involving reinforcement learning research.

Compensation & Benefits

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

Location

Hybrid, with the primary location in New York, New York. Seattle is also listed as a work location.