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Develop and deploy state-of-the-art physical AI for outdoor robotics, focusing on perception, planning, control, simulation-driven training, multi-sensor integration, data pipelines, and GPU-optimized training and inference.

Lead development of scalable simulation and training infrastructure for robot learning. Implement high-fidelity physics, handle multimodal sensor data, build tools for large-scale RL/imitation learning, and optimize software for GPU parallelization. Help shape AI capabilities and grow into leadership roles.

Own end-to-end hardware test strategy for robotic systems, including functional, environmental, vibration, dust, heat, and life-cycle testing. Build fixtures and automation, define acceptance criteria, investigate failures and field incidents, perform root-cause analysis, enforce safety procedures, and produce traceable, data-driven test reports for components, subassemblies, and integrated robots.

The Robotics System Test Engineer will lead test strategies for robotic systems, perform testing in outdoor environments, and ensure safety and reliability for autonomous operations.

Develop and evaluate robot perception components on real-world data: build datasets and evaluation harnesses, run experiments, integrate modules into the live robot stack, and demo on hardware. Work spans pose estimation, VLMs/VLAs, 3D reconstruction, object detection, and multimodal learning; opportunity to publish and attend conferences.

Intern will train and deploy robot policies (imitation learning, RL, or fine-tuned foundation models), build data collection and evaluation pipelines, run ablations, and iterate on real-hardware performance. Work includes pose estimation, vision-language and multimodal methods, 3D reconstruction, object detection, and testing policies on office robots.

Intern will build and operate training, data, and evaluation infrastructure: manage GPU clusters, orchestration, and large-scale data pipelines; instrument, monitor, and harden systems; test on robots; and deliver an end-to-end scoped project with mentorship. Opportunities to publish and attend conferences for qualifying interns.

Design, build, and maintain full-stack cloud applications and real-time frontends to monitor and control robot fleets. Implement scalable ingestion, storage, streaming, and analytics for high-volume telemetry and video. Develop agentic/LLM-based tooling, improve reliability and observability, debug field issues, and ship production software from prototype to deployed systems on construction sites.

Seeking a Perception ML Engineer to develop and deploy advanced perception models for robotics, focusing on manipulation and navigation in dynamic environments.

The Mechanical Engineer will integrate robotic systems onto heavy vehicles, focusing on design, environmental resilience, and field deployment for various construction tasks.