
Flexion Robotics builds software that enables humanoid robots to perform diverse real-world tasks with minimal human teleoperation. It trains models in high-fidelity simulated environments using reinforcement learning and synthetic data generation, combining vision-language-action models and language-based reasoning to interpret instructions and adapt to new settings. The stack includes transformer-based whole-body control for manipulation and locomotion and a robotics autonomy platform designed for deployment across different hardware. Flexion serves industrial and exploration customers seeking advanced robotic automation and adaptable autonomy solutions.

Flexion Robotics builds software that enables humanoid robots to perform diverse real-world tasks with minimal human teleoperation. It trains models in high-fidelity simulated environments using reinforcement learning and synthetic data generation, combining vision-language-action models and language-based reasoning to interpret instructions and adapt to new settings. The stack includes transformer-based whole-body control for manipulation and locomotion and a robotics autonomy platform designed for deployment across different hardware. Flexion serves industrial and exploration customers seeking advanced robotic automation and adaptable autonomy solutions.
Headquarters: Zürich, Switzerland
Founded: 2024
Domain: flexion.ai
Focus: Autonomy stack for humanoid and general-purpose robots using simulation and reinforcement learning
Latest reported raise: $50M Series A (reported Nov 20, 2025)
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Robotics autonomy for humanoid and general-purpose robots; simulation-to-real transfer for manipulation and locomotion.
2024
Robotics Engineering
$50M
Reported $50M Series A; participation named from DST Global Partners, NVentures, Redalpine, Prosus Ventures, Moonfire Ventures
“DST Global Partners; NVentures; Redalpine; Prosus Ventures; Moonfire Ventures”
We are seeking a Manipulation Lead to define and drive Flexion's manipulation stack, with a strong focus on learning-based dexterous control for humanoid robots.
In this role, you will own the technical direction, architecture, and delivery of manipulation capabilities, from research ideas to real-time execution on physical robots.
You will work closely with the perception, controls, and infrastructure teams, and lead the engineers working on dexterous manipulation. This is a hands-on technical leadership role, not a purely managerial position.
Responsibilities
PhD degree in Robotics, Machine Learning, or a related field, with significant hands-on experience in learning-based manipulation.
Deep expertise in dexterous manipulation models, such as:
Diffusion models
Flow matching
Reinforcement learning
Strong understanding of robot control and real-time constraints.
Proven experience deploying learning-based controllers on real robotic hardware.
Excellent proficiency in Python and PyTorch, including training large neural networks.
Solid knowledge of transformers and modern generative models.
Ability to take technical ownership and make high-impact decisions in a fast-moving environment.