Proprioceptive Robotics Controls Engineer

Enact; Zürich; On-site; CHF 140,000 - 190,000; Full time

Benefits offered by this job

Visa sponsorship & relocation benefits

Central Zürich base with prototyping &

Meaningful equity participation

Competitive compensation

Job summary

Enact in Zürich is seeking a robotics systems engineer to develop the proprioceptive motion control layer, enabling high-contact manipulation that is predictable, smooth, and safe across varied conditions.

You will design model- and learning-based estimation and control algorithms, build runtime loops for teleoperation and AI-driven manipulation, and work with hardware and AI researchers to push the performance of the full stack robot system.

Qualifications

• Degree in Robotics, Mechanical Engineering, or related field.
• Strong theoretical and practical grasp of model- and learning-based whole-body control and state estimation.
• Experience with robot simulation environments (MuJoCo, Isaac Sim, or similar) and robot description files (URDF, USD, etc.).
• Proven ability to take complex algorithms from concept through hardware integration to production-ready real-time robot software.

Responsibilities

• Design and implement model- and learning-based estimation and control algorithms, along with runtime loops for teleoperation and AI-driven manipulation from simulation to real robot system.
• Debug and diagnose complex system behaviors spanning hardware, software, and algorithms.
• Own robot bring-up, including validation and refinement of robot model descriptions for simulation and control, addressing sim-to-real gaps.
• Collaborate with hardware and AI researchers to continuously improve the full stack robot system.

Skills

Proficient in Python

Rust or C/C++

Model-based whole-body control

State estimation

Robotics fundamentals

Education

BSc/MSc/PhD in Robotics or Mechanical Engineering

Tools

MuJoCo

Isaac Sim

URDF

USD

MuJoCo XML

Job description

Enact in Zürich is seeking a robotics systems engineer to develop the proprioceptive motion control layer, enabling high-contact manipulation that is predictable, smooth, and safe across varied conditions.

You will design model- and learning-based estimation and control algorithms, build runtime loops for teleoperation and AI-driven manipulation, and work with hardware and AI researchers to push the performance of the full stack robot system.