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 SereactSereact 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 roleThis 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 doBuild 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
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
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
Zurich Area, Switzerland:
This role is based in our Zurich office, offering a vibrant ecosystem for robotics and AI.
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
Skills Required
- MSc or equivalent, in progress, in robotics, mechanical engineering, or a closely related field
- Thesis or capstone project focused on manipulation, teleoperation, or retargeting
- Hands-on experience building a data collection device or system for robot learning, such as UMI or a comparable system
- 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 sufficient to build and maintain infrastructure used by other engineers
- Ability to work independently as an individual contributor in a small, developing team
- Author contribution to a conference submission on manipulation, teleoperation, or retargeting
- Teaching or teaching assistant experience in a robotics course
- Exposure to large-model training
- Example of building something outside a formal role brief to support team needs
Sereact Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Sereact and has not been reviewed or approved by Sereact.
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Retirement Support — The U.S. package includes a 401(k) with a 100% company match up to 6%, signaling strong employer-backed retirement savings. This stands out as generous for a growth-stage startup.
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Healthcare Strength — Comprehensive medical, dental, and vision coverage for employees and dependents is described, indicating broad healthcare support. Such breadth addresses core protection needs across households.
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Leave & Time Off Breadth — 20 days of PTO alongside paid sick leave and paid parental leave are outlined, pointing to a well-rounded time-off offering. These provisions support rest, recovery, and family needs.
Sereact Insights
What We Do
Sereact's mission is to drive your economic growth by closing automation gaps in your intralogistics. Our AI software enables machines to perceive their environment and develop solution strategies on their own, thus qualifying them to become autonomous skilled workers. By leveraging embodied AI for robotics, we ensure that our systems not only think but also physically interact with their surroundings in an intelligent manner. Sereact's AI software for autonomous robotics fully automates pick-and-place processes, making them more efficient, reliable and resilient. Our goal is to optimize your supply chain with minimal integration effort to increase productivity in your warehouse from the first pick while significantly reducing costs.







