About this role
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
401k (no match)
Healthcare (Silver PPO Medical, Vision, Dental)
Lunch and snacks at the office
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.