Member of Technical Staff - Research, Post-Training

We’re building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work.

We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team.

• Improve existing methods and develop new techniques for large-scale model training, optimization, and inference
• Extend models to long-context and long-horizon tasks
• Improve inference-time efficiency, reliability, and robustness in high-stakes real-world deployments