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As a Machine Learning Engineer, you will design and train perception models for robotics, focusing on 3D perception systems. You will tackle complex physical challenges, optimize models for embedded hardware, and collaborate with cross-functional teams.

Join a cutting-edge team deploying autonomous systems on construction machinery, enhancing safety and project efficiency in infrastructure projects.

Develop and scale learning models for behavior cloning and reinforcement learning. Build data pipelines and evaluate model performance for integration into autonomous systems.

The Site Operations Manager will lead the deployment of autonomous construction technology, ensuring site launches, operational performance, and strong partner relationships throughout project lifecycles.

The Hardware Engineer will design, integrate, and validate hardware for autonomous machines, working on system architecture and collaborating with engineers and vendors.

Architect and maintain the embedded Linux stack for autonomous systems, optimize performance, and lead cross-functional technical efforts.

As a Staff Mechanical Engineer, you'll integrate sensors and hardware into autonomous construction machines, ensuring durability and performance through collaboration with various teams and hands-on prototype support.

The role involves integrating simulators into the Cloud platform, ensuring reliable simulation workflows, and collaborating with simulation engineers to optimize efficiency.

The Robotics Application Engineer leads deployment of autonomous excavators, conducts site evaluations, troubleshoots issues, collaborates on technical strategy, and communicates value to customers.

Lead end-to-end product quality across hardware development, manufacturing, supplier quality, reliability testing, and deployed robotic fleets. Establish IQC/IPQC/OQC, quality gates, FMEA and CAPA processes, define validation and test strategies (HALT/HASS, HIL/SIL), drive root-cause analysis, KPIs (yield, DPPM, MTBF/MTTR), and build automated diagnostics and AI-enabled workflows to improve reliability and field uptime.