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Sereact GmbH

Research Engineer (m/f/d)

Remote

Remote eligibility is not stated by the employer.

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PeopleSeek Talent does not submit applications. The button opens the employer's own page; this listing was verified 3 hours ago.

PayNot listed
Work arrangementRemote
Who can applyNot stated by the employer
LevelNot stated
TypeFull time
Occupationresearch engineer
LanguageNot stated
Posted24 October 2026
Last verified3 hours ago
StatusActive

About the role

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

Find more English Speaking Jobs in Switzerland on Arbeitnow

Skills

Software

Listed via Arbeitnow · first seen 25 October 2026 · last verified 28 October 2026

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