Senior Machine Learning Engineer - Sim2Real & Machine Modeling

About the role

The Autonomy team at Gravis Robotics is seeking a Senior Machine Learning Engineer to bridge the sim2real gap for autonomous construction machinery. You will develop machine and dynamics models, define performance metrics, and work closely with autonomy and simulation teams to ensure controllers function effectively on real-world equipment. This role involves end-to-end ownership of data collection and model validation to improve the fidelity of autonomous systems.

Responsibilities

• Build ML models to bridge the sim2real gap and determine optimal architectures based on data.
• Characterize unmodeled effects that impact sim2real transfer and determine necessary data requirements.
• Define performance metrics and validation methodologies for model fidelity.
• Develop methods to detect changes in machine properties over time.
• Collaborate with autonomy and simulation teams to influence controller development.

Required skills

• Python
• PyTorch
• Git
• Time-series modeling
• Dynamical-system data
• Sequence models
• System identification
• State-space approaches

Nice to have

• Reinforcement learning
• Imitation learning
• Learning from demonstration
• Classical system identification
• Control theory
• Hydraulics

Qualifications

• Degree in Computer Science, Robotics, Machine Learning, Engineering, or a related field

About the Company

Gravis Robotics is a high-growth Series A start-up backed by SoftBank that brings Physical AI to the construction industry by turning heavy machinery into autonomous robots. Originating as an ETH Zurich spin-out, the company develops machine-agnostic retrofit kits that enable autonomous operation for excavators and wheel loaders.