Member of Technical Staff, Applied Researcher

About the Role

Join an applied research team working with advanced AI research organizations on challenging post-training problems. This research-first role focuses on reinforcement learning, training data, and experiments that improve model capabilities.

What You'll Do

• Work with research teams to translate open-ended goals into environments, datasets, experiments, and deliverables.

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

• Shape and inspect high-quality 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 measure capability gains.

• Analyze training signals and experiment results across distributed GPU clusters to guide follow-up experiments.

What We're Looking For

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

• Hands-on model training experience in an AI research lab, AI data organization, or comparable setting, or a strong research or model release record on a recognized benchmark.

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

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

• Experience at an advanced AI research organization or a PhD involving reinforcement learning research is relevant.

Compensation & Benefits

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

Location

Hybrid, based in New York, New York. Seattle is also listed as a location.