Hedra · San Francisco
Design and run pre-training and post-training pipelines for action-conditioned world models and VLA models, including fine-tuning and reinforcement learning. Build distributed training infrastructure with PyTorch, FSDP, and DeepSpeed, and generate simulation datasets for sim-to-real transfer. Works with multimodal video, sensor, and action data.
Hedra is a research and infrastructure lab advancing post-training and inference for multimodal and physical AI. Our ambition is to bring recursive self-improvement to models that learn from and interact with the real world.
We combine reinforcement learning research with GPU compute and optimized inference to help teams post-train, serve and continuously improve models they own.
We're backed by Index Ventures, a16z and Abstract Ventures. Our team works fully in person in San Francisco.
We're looking for people with startup experience who take ownership of their work and care deeply about the problems our customers need to solve. You'll help build the technology, products and business that turn this research into a lasting company.
We encourage you to apply even if you don't fully meet all the listed requirements; we value potential and diverse perspectives, and your unique skills could be a great asset to our team.
Compensation: $175K - $275K