Senior RL Engineer - Autonomous Excavation Systems

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

Zusammenfassung

Gravis Robotics in Zurich is seeking a Senior Reinforcement Learning Engineer to advance autonomous excavation systems. You will build data‑driven planning and control modules that run across models and soil conditions.

Join the autonomy team to deploy learned components in production, address sim2real gaps, and mentor junior engineers while collaborating with motion planning and robotics specialists.

Qualifikationen

• 2–5 years industry experience developing Reinforcement learning systems for control and/or planning and deploying them on real robots with a customer.

Aufgaben

• Learning-Based Planning and Control for Real Systems: Develop data driven planning and control systems for autonomous excavation that generalize across machine models and soil conditions.
• Contribute to simulation improvements that reduce or address the sim2real gap.
• Define data collection and curation pipelines for incorporating real data in policy training.
• Design experiments focused on continuous performance and robustness improvements.
• Provide mentorship and supervision for junior team members, interns, and students.

Kenntnisse

Reinforcement learning

Python

C++

PyTorch

GPU-accelerated simulation

Debugging real-world systems

Travel willingness

Tools

IsaacSim/IsaacLab

CARLA

MuJoCo

ROS

Jobbeschreibung

Gravis Robotics in Zurich is seeking a Senior Reinforcement Learning Engineer to advance autonomous excavation systems. You will build data‑driven planning and control modules that run across models and soil conditions.

Join the autonomy team to deploy learned components in production, address sim2real gaps, and mentor junior engineers while collaborating with motion planning and robotics specialists.