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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.

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.

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.

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.

Architect and develop scalable, high-performance robotics software and frameworks for real-world deployments. Optimize system performance, integrate multi-modal sensors, manage real-time data, and contribute across the autonomy stack using simulation and visualization tools.

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

The ML & Cloud Infrastructure Engineer will develop scalable AI and data pipelines, deploy monitoring and CI/CD pipelines, and optimize performance for cloud-based ML applications.

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