Embedded Systems Engineer

at  Gravis Robotics

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 highly skilled and experienced embedded systems engineer to join our team: you will play a crucial role in our autonomous machine projects, focusing on sensor integration, accelerated image processing, deploying machine learning models and parallel programming on embedded Nvidia GPU platforms. You will work closely with a team of talented engineers to develop and integrate systems that enhance the capabilities of our autonomous machines.

REQUIRED QUALIFICATIONS

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
• 2+ years of proven experience with any embedded platform for machine vision in the autonomous vehicle or a similar domain.
• Proven track record of envisioning and driving the setup and improvement of a developer environment for embedded systems.
• Strong expertise in embedded GPU programming and optimization for Nvidia platforms.
• Excellent problem-solving skills and ability to work in a fast-paced environment.
• Strong communication and teamwork skills.

ADDITIONAL BENEFICIAL SKILLS

• Experience in implementing high-reliability applications, such as automotive or aerospace, where strict quality and safety standards are crucial.
• Experience with Nvidia Jetson Orin SoC.
• Familiarity with autonomous vehicle technology and standards.
• Knowledge of machine learning and AI techniques for Robotics.
• Experience with ROS (Robot Operating System) and other robotics frameworks.
• Understanding of image processing and computer vision techniques and algorithms.
• Integrate and calibrate various sensors (e.g., cameras, LiDAR, RADAR) with embedded GPU platforms.
• Capability to implement parallel programming solutions using such as CUDA, OpenCL and Halide frameworks to accelerate processing tasks.
  Don’t meet every requirement? If you’re enthusiastic about this role but your experience doesn’t match every qualification, we still encourage you to apply. You might be the perfect candidate for this or other positions.
  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.

• Implement core autonomous functionalities on embedded platforms for autonomous excavators.
• Establish a solid devops cycle for the embedded system by solving challenges related to cross-compilation, deployment and build infrastructure.
• Collaborate with cross-functional teams to design and implement system architectures for autonomous machine applications.
• Conduct performance analysis and optimization of embedded systems.
• Maintain and improve existing codebases and documentation.
• Stay updated with the latest advancements in autonomous machines/vehicle platforms and related technologies.