Robotics Teleoperation & Manipulation Data Engineer

Sereact GmbH; Zürich; Hybrid; CHF 110.000 - 140.000; Vollzeit

Benefits dieser Stelle

Free meals at workplace

Flexible working hours

Relocation package for Zurich area

Direct collaboration with founders

Zusammenfassung

Sereact GmbH, based in Zurich, is seeking a Research Engineer to own the data generation layer of the VLA stack, focusing on teleoperation hardware/software and data collection infrastructure feeding Cortex. You will map human demonstrations to robot hands and ensure data quality for model training.

Ideal candidates hold an MSc in robotics or related field, have hands-on experience with data collection devices for robot learning, and can work autonomously in a small, evolving team.

Qualifikationen

• MSc (or equivalent) in robotics, mechanical engineering, or related field.
• Hands-on experience building a data collection device or system for robot learning.
• Working knowledge of retargeting algorithms mapping human input to robot hands.
• 1–2 years of robotics/mechatronics/engineering experience.
• Software and systems engineering to build reliable infrastructure.

Aufgaben

• Build and operate teleoperation systems for dexterous manipulation.
• Design and maintain scalable data collection hardware and software.
• Benchmark control and retargeting approaches with rigorous methodology.
• Support the physical robots in Zurich hub and day-to-day control stack work.
• Collaborate with model-training team to define data needs and quality.
• Build tooling or infrastructure to unblock the wider team.

Kenntnisse

Data collection systems

Robotics research

Software engineering

Retargeting algorithms

Individual contributor

Ausbildung

MSc in robotics or related

Tools

Data pipelines

Robot control stack

Jobbeschreibung

Sereact GmbH, based in Zurich, is seeking a Research Engineer to own the data generation layer of the VLA stack, focusing on teleoperation hardware/software and data collection infrastructure feeding Cortex. You will map human demonstrations to robot hands and ensure data quality for model training.

Ideal candidates hold an MSc in robotics or related field, have hands-on experience with data collection devices for robot learning, and can work autonomously in a small, evolving team.