As a Senior Research Scientist, you’ll design, implement, and deploy cutting-edge research in reinforcement learning and post-training at scale, driving innovations that make it into production
Build and deploy state-of-the-art reinforcement learning pipelines at scale
Post-train large (multi-modal) models to align them with human intent and enable general capabilities such as reasoning, pushing the boundaries of model performance, safety, and efficiency
Always keep the entire lifecycle of research and production in mind: from idea conception, theoretical modeling, prototyping, ablation studies, all the way to production deployment
Build and foster external collaborations with academic and industrial partners
Follow scientific and technical standards for experimentation, reproducibility, and model evaluation
Collaborate deeply with Engineering, ML Platform, and HPC teams to deliver robust and reliable model updates to users
QUALITIES WE LOOK FOR
We’re looking for a scientist with a deep technical background, strong leadership skills, and a proven track record of driving research in reinforcement learning or large-scale model alignment to production
We are seeking researchers with a strong practical background, a creative mindset, and a passion for solving hard problems with real-world impact
You have a solid mathematical background and enjoy solving challenging problems, evidenced by a masters degree, diploma, PhD, or equivalent industry experience in mathematics, physics, computer science, or a related field
Deep practical experience in Python and at least one modern machine learning framework such as PyTorch, TensorFlow, or JAX, experience working with large compute clusters and ML infrastructure is a plus
A track record of leading self-directed research projects that go well beyond academic exercises and deliver tangible results
Expertise in deep reinforcement learning (RLHF/RLAIF/RLVR) is a plus
Hands-on experience scaling and deploying LLMs or other foundation models in real-world systems is a plus