About Hedra

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.

What You'll Do:

• Design, implement, and run pre-training and post-training pipelines for action-conditioned world models and vision-language-action (VLA) models
• Develop and refine training methodologies, including fine-tuning, reinforcement learning, and large-scale multimodal learning
• Design and generate training and evaluation datasets from simulation, including environment setup, domain randomization, and sim-to-real transfer strategies
• Build distributed training infrastructure using PyTorch, FSDP, and DeepSpeed
• Work with multimodal data pipelines involving video, sensory inputs, and action sequences
• Evaluate model performance using both benchmark datasets and real-world deployment metrics
• Contributions research publications a plus
• Collaborate with industrial partners to adapt generative models for real-world physical AI applications

Qualifications:

• Experience with pre-training or post-training on large generative models (video, multimodal, or action-conditioned)
• Hands-on proficiency with PyTorch and distributed training frameworks (FSDP, DeepSpeed)
• Strong fundamentals in machine learning, optimization, and large-scale data processing
• Familiarity with VLMs, VLAs, or world models
• Background in robotics, embodied AI, or sim-to-real transfer is a plus
• Experience with video understanding or temporal reasoning is a plus
• BS/MS/PhD in Computer Science, Machine Learning, Robotics, or a related field

Benefits:

• Competitive compensation and equity