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AI Engineer - Dexterous Manipulation at Flexion Robotics

Zurich, Zurich, Switzerland -

Full Time

Start Date

Immediate

Expiry Date

11 Jun, 26

Salary

0.0

Posted On

13 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Dexterous Manipulation, Learning-based Controllers, Real-time Systems, Diffusion Models, Flow Matching, Reinforcement Learning, ROS, Perception Models, Python, PyTorch, Deep Neural Networks, Transformers, Robotics, Data-driven Manipulation

Industry

Robotics Engineering

Description

We are looking for a dexterous manipulation expert to strengthen our team in Zurich. The goal of this position is the development and deployment of state of the art learning-based controllers to interact with the environment and manipulate objects more reliably and flexibly. As all code has to run on real robotic hardware in real time, hands-on robotic experience and knowledge in state of the art models for dexterous manipulation, such as either Diffusion Models, Flow Matching or Reinforcement learning is required. Experience with ROS and perception models is a plus. Particularly: PhD or master's degree in robotics with relevant project experience (e.g. master thesis) on data-driven manipulation or diffusion models. Excellent knowledge of Python, PyTorch and the training of deep neural networks. Hands-on experience for running learning-based controllers on real robot hardware. Good knowledge in diffusion models and transformers. We are looking for a person who enjoys working in a team in a very dynamic and fast-moving environment, and who is able and willing to take ownership of projects and decisions. We at Flexion Robotics (flexion.ai) are a young company in Zurich working on the next generation of humanoid robot software to enable robots to perform useful tasks autonomously. We work dynamically and move fast. The team is still fairly small and every new employee at this stage will have significant ownership of their current project. We offer a competitive remuneration in the form of a competitive base salary and additional components/benefits depending on the specific role and the experience of the applicant.

Responsibilities

The main goal is the development and deployment of state-of-the-art learning-based controllers to achieve more reliable and flexible interaction with the environment and object manipulation. This involves ensuring all developed code runs effectively on real robotic hardware in real time.