Autonomous Construction ML Engineer: Sim2Real & Modeling

Gravisrobotics; Zürich; Vor Ort; CHF 120.000 - 180.000; Vollzeit

Zusammenfassung

Gravis Robotics in Zürich is seeking a machine learning/robotics engineer to advance machine and dynamics modeling for autonomous construction equipment. You will build models to bridge the sim2real gap, select architectures, and validate performance in collaboration with autonomy and simulation teams.

The role emphasizes hands-on experimentation, data-driven decisions, and contributing to the on-site development of robust autonomous systems for heavy machinery.

Qualifikationen

• Degree in Computer Science, Robotics, ML, Engineering or related field.
• Strong Python and PyTorch, and Git skills.
• Solid experience modeling time-series or dynamical-system data from large datasets.
• Strong analytical skills: design experiments, run ablations, and draw defendable conclusions.

Aufgaben

• Build ML models to bridge the sim2real gap.
• Decide architecture (sequence models, state-space) and justify with data.
• Characterize unmodeled effects and sim2real transfer.
• Assess data needs and distributions for coverage.
• Define performance metrics and validation methodology for model fidelity.
• Collaborate with autonomy and simulation teams; influence controllers.
• On-site data collection and experimentation to obtain needed data.

Kenntnisse

Python

PyTorch

Git

Time-series modeling

Analytical reasoning

Ausbildung

Degree in Computer Science, Robotics, ML, Engineering

Tools

Python

PyTorch

Git

Jobbeschreibung

Gravis Robotics in Zürich is seeking a machine learning/robotics engineer to advance machine and dynamics modeling for autonomous construction equipment. You will build models to bridge the sim2real gap, select architectures, and validate performance in collaboration with autonomy and simulation teams.

The role emphasizes hands-on experimentation, data-driven decisions, and contributing to the on-site development of robust autonomous systems for heavy machinery.