Hexagon Robotics
Switzerland
Senior Team Lead, Machine Learning & Physical AI (Humanoid Robotics) - Zürich
Machine Learning Full-time Mid-Senior level 1w ago
- AI
- Deep Learning
- Machine Learning
- Mlops
AI Summary
Develop foundation models powering Flexion's humanoid robots across architecture, pre-training, adaptation, and post-training. Design and evaluate VLA/WAM models, world-action models, training recipes, and continual learning methods. Requires strong Python and PyTorch skills plus experience in multimodal foundation models, world models, robot learning, or RL/post-training.
Key Highlights
Develop VLA/WAM foundation models for humanoid robot control
Lead large-scale pre-training, adaptation, post-training, and continual learning
Evaluate models in simulation and on real robots
Requires Python, PyTorch, and deep learning experience
Locations include Zurich and San Francisco
Key Responsibilities
Design and develop multimodal VLA/WAM foundation models for general-purpose robotic control
Develop and execute large-scale pretraining across diverse robot embodiments, teleoperation, egocentric human data, and simulated experience
Improve data mixtures, training objectives, optimization strategies, and distributed training workflows
Develop predictive world and action models for representation learning, future-state prediction, planning, and robot policy improvement
Develop methods to efficiently adapt pretrained models to new tasks, environments, embodiments, and capabilities
Improve models using real-world and simulated robot experience, including imitation learning, RL, reward/value-guided learning, and specialist-to-generalist distillation
Develop continual learning methods from autonomous rollouts, failures, interventions, and recoveries
Design rigorous experiments and evaluate models in simulation and on real robots
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Technical Skills Required
Benefits & Perks
Competitive compensation
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
401(k) with company contributions
Health, dental & vision coverage with the flexibility to choose your own plan
Open PTO policy & paid company holidays
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Nice to Have
Experience training VLA, VLM, diffusion, flow-matching, video/world models, or other multimodal generative architectures
Experience with distributed training, multi-node GPU systems, large-scale data mixtures, and foundation-model training optimization
Experience with reinforcement learning, offline RL, reward/value learning, specialist distillation, or continual learning
Experience with predictive world models, video generation, latent dynamics, or self-supervised representation learning
Experience with multi-embodiment robot learning, action representations, or adapting policies across different robot platforms
Experience working with teleoperation, egocentric video, simulation, autonomous rollouts, or other large-scale embodied datasets
Experience evaluating learned policies on real robots, particularly humanoids or dexterous manipulation systems
Job Description
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.
The role
As our VLA/WAM Research Engineer, you'll develop the foundation models that power our humanoid robots, spanning model architecture, large-scale pre-training, adaptation, and post-training.
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