AI Research Engineer/Scientist
Flexion Robotics
AI Research Engineer/Scientist
Flexion Robotics
Humanoid-robotics AI brain for autonomy
Flexion Robotics · San Francisco, United States · Full-time · Posted 2026-10-08
Workplace: on_site
Department: AI Engineering
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
We are seeking an expert in robotics foundation models and multi-modal human action data to advance the frontiers of generalizable manipulation. This position bridges the gap between human embodiment and robotic execution by leveraging video demonstrations, wearable capture systems (such as UMI or sensorized gloves), and complementary data sources. You bring a deep understanding of the full lifecycle required to scale dexterous capabilities, spanning the design and deployment of specialized capture devices, dataset curation, and algorithmic and architectural modeling.
As a Research Scientist/Engineer, you will drive large-scale experimentation and deploy breakthrough ideas across core physical intelligence problems. You will own the development of novel systems that turn cutting-edge research into robust, real-world implementations, ultimately pushing the limits of what our hardware can achieve.
Requirements
Preferred qualifications:
Zurich
San Franciso
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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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