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Lead - Dexterous Manipulation

Job in Zürich, 8058, Zurich, Kanton Zürich, Switzerland
Listing for: Flexion Robotics
Full Time position
Listed on 2026-01-01
Job specializations:
  • Engineering
    Robotics, Systems Engineer, Electrical Engineering
Salary/Wage Range or Industry Benchmark: 30000 - 80000 CHF Yearly CHF 30000.00 80000.00 YEAR
Job Description & How to Apply Below
Location: Zürich

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 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
  • Own the full manipulation stack, from problem formulation and data collection to training, deployment, and evaluation on real robots
  • Define the technical roadmap for dexterous manipulation
  • Lead the transition from research prototypes to robust, real‑time controllers running on humanoid hardware
  • Design, implement, and deploy learning‑based manipulation controllers (e.g. diffusion‑based policies, flow matching, RL, or hybrids)
  • Establish best practices for training, sim‑to‑real transfer, evaluation metrics, and debugging on hardware
  • Mentor and guide the engineers working on manipulation
  • Collaborate closely with perception, whole‑body control, and infrastructure teams to enable closed‑loop manipulation
Requirements
  • 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
Benefits
  • Key technical leadership role in a young, fast‑growing robotics company in Zurich
  • Direct influence on the core manipulation capabilities of next‑generation humanoid robots
  • High ownership and autonomy in shaping systems and research direction
  • Competitive compensation, including base salary and additional benefits
Seniority level
  • Mid‑Senior level
Employment type
  • Full‑time
Job function
  • IT Services and IT Consulting

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