AI Engineer

Vor 3 Tagen

Zürich, Schweiz Metric Geo Vollzeit

AI Engineer – Dexterous Manipulation for Robotics We are seeking an AI Engineer specialising in dexterous manipulation to advance the development of state‑of‑the‑art learning‑based controllers for real‑world robotic systems. In this role, you will design, train, and deploy models that enable robots to interact with their environment and manipulate objects with greater reliability, adaptability, and autonomy. You will work closely with robotics, AI engineering, and perception teams to turn SOTA methods into real‑time, production‑ready behaviour on hardware. Responsibilities Develop and deploy learning‑based controllers for dexterous object manipulation on real robotic hardware. Build and optimise models using Diffusion Models, Flow Matching, Reinforcement Learning, or related approaches. Integrate control policies with real‑time systems and ensure robust on‑robot performance. Collaborate with robotics, perception, and software teams to bridge simulation, modelling, and hardware execution. Implement, train, and iterate deep learning architectures in PyTorch. Contribute to system design, experimentation pipelines, and evaluation frameworks. Work with perception pipelines and ROS for end‑to‑end manipulation tasks. Maintain clean documentation, perform code reviews, and support system debugging on hardware. Qualifications PhD or Master’s degree in Robotics or a related field, with strong project or thesis work in data‑driven manipulation or diffusion‑based methods. Excellent proficiency in Python and PyTorch, with experience training deep neural networks. Proven hands‑on experience running learning‑based controllers on physical robot systems. Strong knowledge of diffusion models, transformers, or state‑of‑the‑art manipulation frameworks. Understanding of real‑time constraints, control integration, and hardware–software interfacing. Preferred Experience Experience with ROS, robot perception models, or sensor fusion. Prior work on dexterous manipulation, grasping, or contact‑rich control. Familiarity with Flow Matching, imitation learning, RL, or generative modelling for control. Experience optimising pipelines for on‑robot inference and deployment. Opportunity to join a fast‑moving, early‑stage robotics team where every engineer has meaningful ownership and impact. Work on cutting‑edge humanoid and manipulation technologies with significant technical depth. Dynamic, collaborative environment with quick iteration cycles and high autonomy. Competitive compensation package, including base salary and role‑dependent benefits. If you’re passionate about building real robotic intelligence and want to make a tangible impact on the future of humanoid control, apply now. Location: Zurich, Switzerland. #J-18808-Ljbffr

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