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.