Senior Reinforcement Learning Engineer

Job overview

The Senior Reinforcement Learning Engineer role is listed in Austin, TX; the posting does not specify a work arrangement. Compensation is not specified. Gravis Robotics develops autonomous robots for heavy construction machines, including excavators used in real construction environments. The engineer develops learning-based planning and control systems that work across machine models and soil conditions. The role helps move autonomy technology from research and prototyping toward reliable deployment by improving simulation, incorporating real-world data, integrating learned components, and evaluating system behavior.

What you'll do

• Develop data-driven planning and control systems for autonomous excavation
• improve simulation to address the sim-to-real gap
• define data collection and curation pipelines
• design experiments to improve performance and robustness
• explore adaptive and online reinforcement learning in deployed systems
• mentor junior team members, interns, and students
• integrate learned components into the software stack
• collaborate with excavation and motion-planning engineers
• build evaluation tools.

What we're looking for

Skills & competencies

senior reinforcement learning engineer

robotics

autonomous excavation

planning and control

reinforcement learning

python

pytorch

c++

simulation

austin tx

gravis robotics

travel as required

Work arrangement

• Weekend coverage required

Why this role

The posting calls for experience deploying reinforcement-learning systems on real robots and willingness to travel as required by business projects.

About the employer

Gravis Robotics is hiring for this role. Industry: Engineering Services. Sector: 54.