Company Overview

Our client is an early-stage robotics company developing autonomy and intelligent assistance systems for large-scale mobile machinery. By combining learning-based automation with advanced remote operation, thier technology enables a single operator to safely supervise and control multiple machines in complex, real-world environments.

The team brings deep academic and industrial expertise in large-scale robotics and perception, and is focused on transitioning state-of-the-art research into production systems deployed on real machines operating in demanding conditions.

Role Overview

This role sits at the intersection of perception, state estimation, and real-world deployment. You will contribute to the design, implementation, and deployment of advanced localization and mapping solutions for autonomous and semi-autonomous heavy machines.
The systems you work on integrate multiple sensing modalities—spanning lidar, vision, inertial sensing, and satellite positioning—into a hardware-agnostic autonomy stack that can be adapted to a wide range of machine types and vintages. The role requires not only strong algorithmic expertise, but also a focus on production-quality software and system robustness.

Key Responsibilities

• Design, prototype, and deploy real-time localization, mapping, state estimation, and calibration algorithms for large autonomous mobile platforms
• Develop SLAM pipelines leveraging lidar, inertial, visual, and GNSS data sources
• Optimize system performance, robustness, and reliability under real-world operating conditions
• Define and maintain testing procedures, validation strategies, and performance metrics
• Collaborate closely with engineers across perception, controls, systems, and hardware to improve end-to-end autonomy performance
• Ensure high-quality, maintainable implementations suitable for deployment on production systems

Required Qualifications

• Master’s or PhD in Computer Science, Robotics, Electrical Engineering, Mechanical Engineering, or a related field
• 3 years of hands-on experience developing and deploying localization and mapping systems
• Strong experience implementing SLAM and state estimation algorithms using lidar-inertial-visual sensor fusion
• Proficiency in C and Python, with a focus on production-grade software development
• Experience working in Linux-based development environments
• Ability to manage technical risk, re-prioritize work, and meet deadlines in a fast-paced engineering environment
• Strong communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences

Nice to Have

• Experience integrating RADAR and/or GPS/GNSS into localization or SLAM systems
• Familiarity with ROS2 and modern robotics middleware