Systems Engineer; Excavator Automation

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 experience honing the cutting edge of large-scale robotics, and is rapidly growing to bring that expertise into a trillion dollar industry.

The autonomy team at Gravis builds autonomous systems for excavators operating in real construction environments. This role is at the intersection of system engineering, integration, field deployments, and debugging
.
We are looking for an engineer with a degree in Electrical Engineering, Mechanical Engineering, Robotics or relevant fields and at least 2 years of practical, hands‑on experience working with real systems – and if they fail, you can help us figure out why. This is not an entry‑level or new‑graduate role
.

You will help define and execute system‑level test scenarios, support atypical and beta deployments, and act as a technical bridge between the field and the engineering team. You will help train our field engineers and keep them in touch with fast evolving autonomy capabilities.

• Validate system behavior across machines, environments, and operating conditions
• Identify edge cases, failure modes, and operational limits
• Collaborate with engineering teams on making technical decisions on a system level
• Investigate system failure during field testing or deployments
• Apply hotfixes when appropriate
• Support or conduct deployments if needed, especially pilots or beta customers
• Support/conduct atypical deployments, pilots, and beta customers
• Capture lessons learned from deployments and feed them back into system testing and design
• Help prioritize fixes and improvements based on real‑world impact

• Bachelor’s degree in Electrical Engineering, Mechanical Engineering, Robotics, or a closely related field
• 2+ years of hands‑on experience working with complex systems (automation, robotics, vehicles, heavy machinery, industrial equipment, or similar)
• Strong system‑level troubleshooting and debugging skills
• C++ and Python programming skills, proficiency in git systems
• Proficiency in Linux systems
• Comfortable working in field environments (construction sites, test yards, deployments)
• Ability to travel abroad, according to needs of the business
• Driver’s license B category

• Experience with excavators, heavy equipment, or off‑road vehicles
• Field testing experience
• Familiarity with communication technologies such as DDS, Zenoh, LCM, etc.
• Experience in motion planning or control
• Experience in robotic competitions

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, analysing resumes, or assessing responses. 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.