Member of Technical Staff, Applied Researcher

About the Role

Join an applied research team working directly with frontier AI labs on challenging post-training problems. This research-focused role turns open-ended goals into experiments, training data, and measurable improvements in model capabilities.

What You'll Do

• Partner with customer research teams to translate research goals into concrete environments, datasets, experiments, and deliverables.

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

• Inspect and shape high-fidelity trajectories and training data, with careful attention to correctness and edge cases.

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

• Review training signals and experiment results across distributed GPU clusters to guide the next research iteration.

What We're Looking For

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

• Hands-on model training and reinforcement learning experience in a frontier AI lab, research-focused AI organization, or AI data lab, or a strong research publication or model release with notable benchmark results.

• Practical experience with post-training methods, training data, and model evaluation; this is a research role, not a general machine learning engineering position without reinforcement learning experience.

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

Compensation & Benefits

Salary range: $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 location.