Sim2Real ML Engineer for Autonomous Heavy Machinery

Carbon Data Solutions; Zürich; Vor Ort; CHF 110.000 - 170.000; Vollzeit

Zusammenfassung

Gravis Robotics is hiring for an autonomy-focused role that strengthens the sim2real gap for autonomous controllers in heavy machinery. You will develop ML models, assess architectures, and work closely with autonomy and simulation teams to influence on-machine controllers.

The ideal candidate has a strong ML/RL background, experience with real robotic systems, and solid Python/PyTorch skills. A degree in CS/Robotics/Engineering is required, and a hands-on, data-driven approach is valued.

Qualifikationen

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

Aufgaben

• Build ML models to bridge the sim2real gap for autonomous controllers.
• Decide and justify architectures (sequence models, state-space, etc.) with data.
• Characterize unmodeled effects and data distributions needed.
• Define performance metrics and validation for model fidelity and sim2real transfer.

Kenntnisse

Python

PyTorch

Git

Time-series modeling

Robotics

Ausbildung

Bachelor’s/Master’s in CS/Robotics/Engineering

Jobbeschreibung

Gravis Robotics is hiring for an autonomy-focused role that strengthens the sim2real gap for autonomous controllers in heavy machinery. You will develop ML models, assess architectures, and work closely with autonomy and simulation teams to influence on-machine controllers.

The ideal candidate has a strong ML/RL background, experience with real robotic systems, and solid Python/PyTorch skills. A degree in CS/Robotics/Engineering is required, and a hands-on, data-driven approach is valued.