Internship - Humanoid Motion Generation (Diffusion or Flow Matching)

ph3About Flexion: /h3 pAt 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 deployment of humanoids. We are founded by leading scientists in robot reinforcement learning (ex-Nvidia, ex-ETH Zürich) and backed by leading international VC firms. Within a few months, we’ve gone from our first line of code to deploying real humanoid capabilities with our partners. /p h3The Role: /h3 pWe’re looking for a talented MS or PhD intern to join our team in Zürich and push the boundaries of how humanoid robots perceive and interact with the world. /p pYou will work at the intersection of generative whole-body trajectory generation (using diffusion models, flow matching, and/or auto-regressive models) and 3D environment perception. /p pIf you enjoy solving open-ended problems in a fast-moving environment, this is a unique opportunity to learn from our world‑class team of engineers and scientists, and contribute to our foundational software development. /p pRequired skills: /p ul liCurrently pursuing a Master’s or PhD degree in Computer Science, Robotics, Machine Learning, or a related technical field. /li liExperience in diffusion models/flow matching or learning-based trajectory generation with relevant project experience. /li liFamiliarity with generative modeling and its application to time series data. /li liExcellent Python and PyTorch skills; comfortable writing clean, modular code for rapid experimentation. /li liStrong, proven analytical thinking and problem-solving skills. /li liAbility to navigate and implement state-of-the-art methods from recent literature. /li liPreferably: autonomous research/project work in human motion generation (neural avatars), robotic imitation learning, or ego‑centric action prediction. /li /ul pAdditionally, the following skills are a plus but not required: /p ul liExperience in robotics. /li liExperience with simulation environments. /li liExperience with multi‑modal generative models. /li liExperience with finetuning foundation models, e.g., Gr00t or SmolVLA, to produce whole‑body actions or kinematics motions. /li /ul ul liCompetitive compensation /li liA front‑row seat at one of Europe’s most ambitious robotics companies /li liAn energetic, collaborative team with a bias for action /li /ul /p