Robotics Engineer – Autonomous excavation

2 мес. назад

SwitzerlandEuropeOnsite

Engineer developing autonomous robotics for heavy construction machinery.

О компании

Gravis Robotics is a startup that turns heavy construction machines into autonomous robots. Our unique combination of learning-based automation and augmented remote control lets one operator safely conduct a fleet of earthmoving machines in a gamified environment. Our team has over a decade of academic experience honing the cutting edge of large-scale robotics, and is rapidly growing to bring that expertise into a trillion dollar industry through active deployments with market leaders.

Обязанности

  The autonomy team at Gravis builds autonomous systems for excavators operating in real construction environments. You will build control modules that run on many different machines , across many sites, with different soil conditions. We’re looking for a roboticist with data driven planning and/or control background, deep python expertise and good level of C++ proficiency.   To be successful in this role you should have experience working with real robots, tackling the challenges of sim2real transfer, and deploying robotic systems in a production environment.   The autonomy team at Gravis builds autonomous systems for excavators operating in real construction environments. In this role, you will develop control modules designed to run across diverse machines, sites, and soi
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.
Explore the usage of adaptive and online reinforcement learning in deployed systems
Provide mentorship and supervision for junior team members, interns, and students.
Integrate learned components into a larger software stack
Collaborate with excavation and motion planning engineers
Build tools for analysing and evaluating the behavior of learned components

Другое

2–5 years industry experience developing Reinforcement learning systems for control and/or planning and deploying them on real robots with a customer. If you only have experience with simulation, you’re most likely not a good fit for this position.
Experience with GPU accelerated simulation environments (e.g. IsaacSim/IsaacLab, CARLA, MuJoCo)
Strong Python skills and experience with PyTorch or similar libraries
Proficiency in C++
Comfortable debugging real-world system behavior
Ability and willingness to travel as required by business projects. 
Experience with hydraulic machinery
Experience with supervised learning or imitation learning
Research experience in reinforcement learning
Experience deploying robotic systems at scale (e.g. hundreds of units)
Familiarity with ROS or similar robotics frameworks
Experience with feature-flagged deployments, staged rollouts, or long-lived platforms
Experience with data curation for ML applications
Experience guiding, mentoring, or leading junior colleagues, students, or project teams. 
Familiarity with or interest in utilizing AI coding tools. 
You are passionate about building systems that work reliably in the real world
You want to help build a long-lived excavation planning and control system intended to scale and positively impact the entire construction industry. 
You are comfortable working with the realities of imperfect data and noisy measurements.
You have a keen interest in bridging the sim2real gap and understanding the differences between simulation and physical environments. 
You are excited to help drive technical direction in a growing team transitioning from prototyping to the product stage.
You value a collaborative team culture rooted in thoughtful design, creative thinking, mutual respect, and pragmatism.