Hedra is building a world-class Physical AI research team to push the boundaries of action-conditioned world models and generative AI for physical systems. As a Researcher, you will drive original research into the intersection of generative modeling, embodied AI, and real-world physical applications alongside industrial partners. You will have access to large-scale compute, the freedom to pursue high-impact research directions, and a direct path to publication at top venues. We are looking for researchers who are excited to go beyond benchmarks and build models that operate in the real world — drawing on Hedra’s leadership in generative modeling and the depth of our academic partnerships, including connections to Fei-Fei Li and the Stanford Vision & Learning Lab.
Responsibilities:
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Define and lead research directions in action-conditioned world models, physical AI, and generative modeling for embodied systems
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Design novel architectures, training objectives, and evaluation frameworks for VLMs, VLAs, and world models
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Direct research efforts with the goal of publishing in top journals.
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Partner with industrial collaborators to ground research in real-world physical AI use cases
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Mentor research engineers and collaborate cross-functionally to move research into production
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Stay at the frontier of the field — synthesizing relevant literature and identifying opportunities for impactful contributions
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Contribute to Hedra’s research culture and external scientific reputation
Qualifications:
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PhD in Machine Learning, Computer Science, Robotics, or a related field, with publications at top ML or robotics venues
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Deep expertise in generative modeling, world models, or vision-language(-action) models
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Strong publication record at NeurIPS, ICML, ICLR, CVPR, CoRL, or equivalent venues
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Experience with large-scale model training and modern deep learning infrastructure
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Ability to independently drive research projects from ideation through publication
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Background in embodied AI, robotic manipulation, or sim-to-real transfer is highly desirable
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Experience with RLHF, DPO, or preference optimization for model alignment is a plus
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Strong collaboration and communication skills — comfortable bridging research and applied teams
Benefits:
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Competitive compensation and equity
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401k (no match)
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Healthcare (Silver PPO Medical, Vision, Dental)
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Lunch and snacks at the office
Legal
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.