About Enact
The next defining technological breakthrough will be in the physical world. We stand at a historical inflection point: bringing general-purpose intelligence into robotics.
At Enact we rethink the entire robotic tech stack from model architectures and data pipelines, to the actuators and sensors that feed the model. Pushing beyond pure vision and language approaches, we build a proprioceptive nerve system, and the cortex that makes sense of it, to solve dexterity through whole-body force-awareness and deploy robots for thousands of tasks in industry and beyond.
We are shaping a company where brilliant and unconventional people thrive together on solving the hardest challenges of our time. We are truth seekers. We reason from first principles, test our beliefs against reality, and trust that the best ideas can come from anyone. We move fast. We care deeply about our work and colleagues and are driven by passion to change the status quo.
If this resonates, we're excited to hear from you.
In This Role
You will develop the proprioceptive motion control layer to enable our robots to do high contact manipulation predictably, smoothly, and safely under varied and uncertain conditions.
Design and implement model- and learning-based estimation and control algorithms, along with the runtime loops that form the backbone for teleoperation and our AI-driven manipulation, from simulation to the real robot system.
Debug and diagnose complex system behaviors spanning the interplay of hardware, software, and algorithms.
Own robot bring-up, including validation and refinement of our robot model descriptions (URDF, MuJoCo XML, USD, etc.) for simulation and control, characterizing and adjusting for the sim-to-real gap as needed.
Work together with both our hardware team and our AI researchers to continuously assess and push the performance of our full stack robot system
What We're Looking For
Degree (BSc/MSc/PhD) in Robotics, Mechanical Engineering, or a related field
Excellent 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
Strong proficiency in Python, complemented by efficient low-level programming skills in Rust or C/C++
Bonus Points If You Have
Hands-on experience with tensor and automatic differentiation frameworks such as JAX, PyTorch, CppAD, Burn, or similar.
Experience with whole-body force estimation
Experience in developing reinforcement learning based robot control
Experience in robot safety, including Control Barrier Functions and/or relevant industry certifications.
Experience in contact rich manipulation, preferably including teleoperation and interfacing with large behavior models such as VLAs.
What we offer
The opportunity to make a real impact working on some of the biggest challenges of our time
A fast-paced learning environment alongside an outstanding, driven team
Ownership from day one, with the ability to iterate quickly and see your impact firsthand in an early-stage startup
Visa sponsorship & relocation benefits to hire the best in the world
A world-class in-person setup in central Zürich, with excellent prototyping, robotics, and technical infrastructure for hands-on builders
Competitive compensation and meaningful equity participation
Skills Required
- BSc, MSc, or PhD in Robotics, Mechanical Engineering, or a related field
- Strong theoretical and practical understanding of model- and learning-based whole-body control and state estimation
- Experience with robot simulation environments such as MuJoCo or Isaac Sim
- Experience with robot description files such as URDF or USD
- Ability to take complex algorithms from concept through hardware integration to production-ready real-time robot software
- Strong proficiency in Python
- Efficient low-level programming skills in Rust or C/C++
- Experience with tensor and automatic differentiation frameworks such as JAX, PyTorch, CppAD, or Burn
- Experience with whole-body force estimation
- Experience developing reinforcement-learning-based robot control
- Experience in robot safety, including Control Barrier Functions or relevant industry certifications
- Experience with contact-rich manipulation, teleoperation, or VLAs
What We Do
Enact Intelligence is a Zurich-based robotics company developing an integrated technology stack for dexterous robots. It combines model architectures, data pipelines, actuators, and sensors into a proprioceptive “nerve system” and “cortex” for whole-body force awareness. Its goal is to deploy robots capable of performing thousands of industrial and other tasks, with a team drawn from robotics, AI, and engineering organizations.
