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Machine Learning Engineer
Gravis Robotics
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Gravis Robotics is a startup that turns heavy construction machines into intelligent and autonomous robots.  Our unique combination of learning-based automation and augmented remote control lets one operator safely conduct a fleet of machines in a gamified environment—from anywhere in the world.  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.

About the Job
At Gravis, we make the heaviest machines move through dirty and dynamic environments with style and grace, by leveraging advanced learning-based methods for planning and control.  We are looking for a motivated software engineer with a background in deep reinforcement learning to augment our team, and to help teach our machines the art of moving mountains.  In this role, you will contribute to developments that improve a range of activities, from high-level task planning to navigation and control.


    • University degree in Computer Science, Robotics, or a related field
    • Proficiency with C++, Python, and Git
    • Experience with large-scale robotics simulation, sim-to-real transfer
    • Experience with synthetic data generation and augmentation
    • Familiarity with popular deep learning libraries (TensorFlow, PyTorch, etc.) and  ROS/ROS2
    • Expertise in algorithm tuning and optimization (reward shaping, hyperparameter tuning, etc.)
    • Experience with hardware deployment, beneficial
This is an opportunity to join a dynamic and versatile team, and to be part of a young startup that will revolutionize heavy construction.  Gravis Robotics offers a fair market salary and a working location in the vibrant heart of Zurich.  As a forward-facing startup, we understand that work-life balance and flexibility are important considerations for many professionals:  If you are a highly qualified candidate with the requisite skills and experience, we encourage you to apply and discuss your preferred working arrangement during the interview process.

Gravis is an equal opportunity employer. We are committed to building an inclusive and diverse team, and do not discriminate based upon race, color, ancestry, national origin, religion, sex, sexual orientation, age, gender identity, gender expression, disability, veteran status, or other legally protected characteristics.

We are an international team that is working to solve problems with a global impact:  to facilitate efficient communication and collaboration, proficiency in English is a requirement for all roles.
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Part time
Mid Level
Reinforcement Learning