Research Engineer (m/f/d)
At a glance
Mid-level AI Research role at Sereact. Zurich · full-time.
Pay not stated Research Engineer salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build and run teleoperation systems that transfer human hand and arm movements to robot end-effectors
- Create and maintain UMI-style data collection hardware and software for other engineers to use
- Compare control and retargeting methods with rigorous evaluations informed by human factors
- Keep Zurich hub robots and their control stack working, while helping set data needs and quality with the training team
What you bring
- An MSc, or equivalent qualification in progress, in robotics, mechanical engineering or a related field, with relevant project work
- Practical experience creating a robot-learning data collection system, plus working knowledge of retargeting human input for robot hands
- One to two years across research, internships or industry in robotics, mechatronics or a related engineering area
- Systems and software skills to build and support infrastructure used by other engineers
Who this fits
This is a mid-level individual contributor role for someone who can build practical robotics systems as well as research methods. You'll work from the Zurich office, with work-from-home flexibility when needed.
From the employer
Research Engineer, Manipulation Data & Teleoperation — Zurich
This role owns the data generation layer of Sereact's VLA stack: teleoperation systems and data collection infrastructure that feed Cortex, built from our Zurich research hub.
About Sereact
Sereact is a Series B embodied-AI company. Cortex, our VLA model, is deployed in live warehouse robotic cells across the EU and US. Zurich is our newest research hub, focused on the manipulation and control problems that sit underneath Cortex.
The role
This is a Research Engineer position. It is scoped to the data generation layer of the VLA stack: teleoperation hardware and software, retargeting pipelines that map human demonstrations onto robot hands, and the data collection infrastructure that feeds Cortex. It requires building the systems that produce the data those models train on, and working closely with the training team on what that data needs to look like.
What you'll do
Build and operate teleoperation systems for dexterous manipulation, including retargeting algorithms that map human hand and arm motion onto robot end-effectors
Design and maintain scalable, UMI-style data collection hardware and software that other engineers at Sereact rely on
Benchmark control and retargeting approaches using rigorous, human-factors-informed methodology
Instrument and support the physical robots deployed in the Zurich hub, including day-to-day work on the control stack
Work with the model-training team to define what data they need and close the loop on data quality
Build tooling or infrastructure outside your immediate brief when it unblocks the wider team
What you'll bring
MSc (or equivalent, in progress) in robotics, mechanical engineering, or a closely related field, with a thesis or capstone project on manipulation, teleoperation, or retargeting
Hands-on experience building a data collection device or system for robot learning (UMI or a comparable system), not just operating one someone else built
Working knowledge of retargeting algorithms for mapping human input onto robot hands or end-effectors
1 to 2 years of combined research, internship, or industry experience in robotics, mechatronics, or a related engineering discipline
Software and systems engineering skills strong enough to build and maintain infrastructure other engineers rely on, not only research-grade prototypes
Comfortable working as an individual contributor in a small, still-forming team
Nice to have
A conference submission on manipulation, teleoperation, or retargeting where the candidate is an author (an MSc thesis submitted to a venue like CoRL counts; supervising a student team whose own work was later published does not)
Teaching or TA experience in a robotics course
Some exposure to large-model training, even without an independent training record
A concrete example of building something outside the formal role brief because the team needed it
Location:
Zurich Area, Switzerland:
This role is based in our Zurich office, offering a vibrant ecosystem for robotics and AI.
What We Offer:
Free meals at the workplace.
Flexible working hours and the option to work from home when needed.
Direct collaboration with founders and world-leading AI experts.
Access to large-scale compute clusters and proprietary robotic datasets.
A key role in shaping the future of embodied AI.
Competitive compensation and a relocation package for the Zurich area