Embodied AI Robotics Engineer

Location: San Francisco, California, United States; full-time onsite work five days a week. Domestic relocation assistance is available. Visa sponsorship is not available.

Salary: $107,280–$174,330 per year

Company

Builds technology that connects machines, data, and people through physical systems, software, connectivity, autonomy, and AI.

What you will do

• Develop, test, validate, and deploy AI and autonomy capabilities for robotic systems.
• Apply machine learning, computer vision, foundation models, and related technologies to engineering problems.
• Integrate perception, planning, reasoning, and control capabilities.
• Design algorithms, models, system components, simulation scenarios, benchmarks, regression tests, and on-machine evaluations.
• Troubleshoot software, model, sensor, compute, and machine-behavior issues while optimizing systems for edge deployment.
• Collaborate with software, hardware, infrastructure, research, validation, safety, and product teams to deliver and maintain production-quality solutions.

Requirements

• Bachelor’s degree in Computer Science, Robotics, AI, Machine Learning, Electrical Engineering, or a related field.
• Experience developing software, robotics, AI, or autonomous systems through industry, academic research, internships, or substantial project work.
• Strong software engineering fundamentals in Python, C++, or similar languages.
• Experience developing, integrating, and testing production-quality systems.
• Ability to solve ambiguous technical problems, make sound engineering tradeoffs, and collaborate across teams.
• Ability to work onsite in San Francisco five days per week; visa sponsorship is not available.

Nice to have

• Experience with ROS/ROS2, motion planning, SLAM/localization, manipulation, or controls.
• Expertise with LLMs, vision-language models, vision-language-action models, multimodal learning, or generative AI for robotics.
• Background in deep learning, reinforcement learning, imitation learning, self-supervised learning, or representation learning.
• Experience with computer vision, sensor fusion, object detection and tracking, or 3D scene understanding.
• Experience with distributed systems, AI infrastructure, large-scale training, edge deployment, or performance optimization.

Culture & Benefits

• Work with real-world data from more than 1.6 million connected assets.
• Medical, dental, and vision benefits, paid time off, holidays, and volunteer time.
• 401(k) savings plans, HSA, FSA, disability benefits, and life insurance.
• Career development, tuition reimbursement, incentive bonus, employee discounts, and wellness programs.
• Parental and adoption benefits, plus an employee assistance program.