Robotics Manipulation Intern
Flexion Robotics
Robotics Manipulation Intern
Flexion Robotics
Humanoid-robotics AI brain for autonomy
Flexion Robotics · Zürich, Switzerland · — · Posted 2026-11-02
Workplace: on_site
Department: AI Engineering
About Flexion:
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 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.
The Role:
We are looking for a motivated intern to join our manipulation team and contribute to the development and deployment of learning-based controllers for dexterous manipulation on our humanoid robot.
You will work closely with top engineers and researchers across our manipulation, reinforcement learning, and motion generation teams. This is a hands-on role where you will gain real-world robotics experience by contributing to state-of-the-art research and development initiatives - from training models to deploying them on physical hardware.
If you are passionate about pushing the boundaries of humanoid dexterous manipulation and want to learn from one of the leading teams in the field, this is the role for you.
Currently pursuing a PhD, or a Master's student close to graduation in robotics, core ML, computer vision, or a related field
Excellent knowledge of Python and PyTorch
Additionally, the following skills are a plus
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Humanoid-robotics AI brain for autonomy
Flexion Robotics builds the AI brain for humanoid robots, enabling autonomy by letting robots understand natural-language tasks, plan motions, and control their bodies through reinforcement learning and sim-to-real training. Its stack includes a command layer that uses language models for task decomposition, a motion layer with vision-language-action models trained largely on synthetic data, and a low-latency whole-body control layer with modular skills. The company differentiates itself with an ETH Zurich–trained engineering team and a full-stack approach that covers language, motion, and real-time control, plus active funding and OEM partnerships. Its goal is to enable useful, widespread autonomy for humanoid robots by partnering with original equipment manufacturers to scale robot fleets and establish a US presence.
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