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 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.
About the Job
At Gravis, we engineer solutions at the nexus of hardware and software every day: bringing new perception and control technologies onto awesome, autonomous machines. Our Rooftop Autonomous Control Kit (Rack) combines sensors, compute, communication and networking modules toward a manufacturer-agnostic solution that can be applied to a variety of construction machines regardless of type and age. We are seeking a skilled SLAM Engineer for our perception team: you will help design, develop, test and deploy customized forms of state-of-the-art localization+mapping, state estimation and calibration algorithms—while ensuring production quality implementation and timely execution.
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Design, prototype, and deploy advanced real-time localization, mapping, and calibration systems for autonomous heavy machines, by means of lidar, inertial, visual and GPS data.
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Establish and optimize testing procedures and performance metrics to ensure robust system behavior.
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Collaborate closely with multidisciplinary experts to improve the reliability and performance of the entire system.
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Master’s or PhD in Computer Science, Mechanical Engineering, Electrical Engineering or a related field.
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3+ years of experience in developing and implementing robust localization + mapping algorithms.
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Experience writing production-quality C++/Python code in a Linux development environment.
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Experience with building/refining SLAM frameworks using Lidar-Intertial-Visual data.
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Risk management skills with the ability to re-prioritize work packages and meet deadlines in a fast paced work environment.
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Excellent communication skills with the ability to effectively convey technical concepts to both technical and non-technical stakeholders.
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Experience with RADAR and GPS/GNSS integration into SLAM systems.
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Experience with ROS2.
Don't meet every requirement? If you're enthusiastic about the role but your experience doesn't match every qualification, we still encourage you to apply. You may still be the perfect fit for another position - tell us about how you could accomplish your best at Gravis with a cover letter.
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 city 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.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
