Research Scientist

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

• Define and lead research directions in action-conditioned world models, physical AI, and generative modeling for embodied systems
• Design novel architectures, training objectives, and evaluation frameworks for VLMs, VLAs, and world models
• Direct research efforts with the goal of publishing in top journals.
• Partner with industrial collaborators to ground research in real-world physical AI use cases
• Mentor research engineers and collaborate cross-functionally to move research into production
• Stay at the frontier of the field — synthesizing relevant literature and identifying opportunities for impactful contributions
• Contribute to Hedra's research culture and external scientific reputation

Qualifications

• PhD in Machine Learning, Computer Science, Robotics, or a related field, with publications at top ML or robotics venues
• Deep expertise in generative modeling, world models, or vision-language(-action) models
• Strong publication record at NeurIPS, ICML, ICLR, CVPR, CoRL, or equivalent venues
• Experience with large-scale model training and modern deep learning infrastructure
• Ability to independently drive research projects from ideation through publication
• Background in embodied AI, robotic manipulation, or sim-to-real transfer is highly desirable
• Experience with RLHF, DPO, or preference optimization for model alignment is a plus
• Strong collaboration and communication skills — comfortable bridging research and applied teams

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.