Research Scientist
Leads original research in action-conditioned world models, physical AI, and generative modeling for embodied systems. Requires PhD in ML/CS/Robotics with top publications and expertise in generative models and large-scale training.
About the job
Responsibilities
- 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
Skills
Generative Modeling, World Models, Vision-Language Models, Vision-Language-Action Models, Large-Scale Model Training, Deep Learning, Embodied Ai, Robotic Manipulation, Sim-To-Real Transfer, RLHF, Dpo, Preference Optimization
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