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About the Role
We are seeking an expert in dexterous manipulation and large-scale modeling to lead the development of our physical foundation models. The goal of this position is to leverage internet-scale egocentric video to build Vision-Language-Action (VLA) models that enable our humanoid robots to interact with the world with human-like fluidity. You bring a deep understanding of how to bridge the gap between observing human actions in video and executing high-DOF (20+) motor control.
Responsibilities
- Architect and implement large-scale pre-training objectives for egocentric video datasets to learn generalizable representations of hand-object interactions and spatial-temporal dynamics.
- Develop and scale multi-modal Foundation Models that unify visual perception and natural language instructions into actionable robotic trajectories.
- Design and optimize generative action heads using Diffusion Models and Flow-matching techniques to capture the multi-modal distribution of complex human movements.
- Develop novel algorithms to align human-centric video representations with the kinematic constraints of 20+ DoF humanoid systems, ensuring fluid and stable execution.
- Utilize Offline RL and high-fidelity simulation fine-tuning to optimize foundation model performance for high-success-rate physical manipulation.
- Translate cutting-edge research in scaling laws and world models into production-ready architectures that enhance robot reliability and autonomy.
Requirements
- PhD or Master’s degree in Robotics, Machine Learning, or a closely related field, with a strong focus on data-driven manipulation, egocentric vision, or foundation models.
- Experience with Humanoid or Dexterous Manipulation, including a deep understanding of contact-rich physics.
- Excellent knowledge of Python, PyTorch, and the distributed training of large-scale neural networks (FSDP, NCCL).
- Proven expertise in Diffusion Models, Flow Matching, and Transformers.
- Hands-on experience deploying learning-based controllers on real robot hardware.
- Experience with Reinforcement Learning and simulation environments (e.g., IsaacLab, MuJoCo)
Skills
- Dexterous manipulation
- Large-scale modeling
- Vision-Language-Action (VLA) models
- High-DOF (20+) motor control
- Egocentric video
- Foundation models
- Diffusion Models
- Flow Matching
- Transformers
- Python
- PyTorch
- Distributed training
- FSDP
- NCCL
- Reinforcement Learning
- Offline RL
- Simulation environments
- IsaacLab
- MuJoCo
Location
- Zürich
Work Type
- Onsite
- Full-time
Experience Level
- Expert
Education Level
- PhD
- Master's degree
Salary/Compensations
- Competitive compensation
Benefits
- Enhanced pension plan
- Enhanced holiday & paid leave perks
- Relocation & permit sponsorship
- Central Zürich office with top-tier robotics testing facilities and infrastructure
- Joining Europe's leading robotics team & exposure to never-done-before research
- Energetic, collaborative culture with a bias for action and regular community events
About the Company
- At Flexion, we're building the intelligence layer powering the next generation of humanoid robots.
- Our mission is to accelerate the transition from fragile prototypes to real-world humanoid deployment.
- We are founded by leading scientists in robot reinforcement learning (ex-Nvidia, ex-ETH Zürich), and backed by leading international VC firms.
- In just months, we’ve gone from our first line of code to deploying real humanoid capabilities.