You will deploy computer-vision-enabled robotic systems into real production environments. You will work directly with customers, integrate robots with their operations, and solve the practical perception, calibration, controls, and reliability problems that appear outside the lab.

What You Will Do

• Build hybrid robotic systems that combine classical robotics with modern AI models.
• Develop reliable planning, perception, calibration, control, and safety tools that AI systems can call and use.
• Decide which parts of a task should be learned and which should remain deterministic.
• Integrate cameras, sensors, robots, controllers, and customer infrastructure into complete working systems.
• Design evaluation frameworks that measure task success, accuracy, cycle time, robustness, interventions, and failure rates.
• Instrument deployed systems, analyse failures, and identify whether improvements require better models, data, controls, or system design.
• Deploy systems at customer sites and improve them until they operate reliably under real production conditions.
• Turn solutions developed for individual deployments into reusable Atlas capabilities.

Requirements

• Hands-on experience deploying robots that use computer vision in real-world environments.
• Strong understanding of classical robotics, including coordinate frames, calibration, kinematics, controls, and motion planning.
• Practical computer-vision experience with cameras, detection, tracking, pose estimation, or visual servoing.
• Strong Python skills and working knowledge of C++.
• Experience with ROS or comparable robotics frameworks.
• Comfortable working directly with hardware and debugging systems under real operational constraints.
• Willingness to travel regularly to customer sites.
• High ownership and clear communication.

Nice to Have

• Experience in industrial automation, manufacturing, logistics, or warehouse robotics.
• Familiarity with industrial robot arms, PLCs, safety systems, or fieldbus protocols.
• Experience deploying perception systems under changing lighting, occlusion, or latency constraints.
• Previous customer-facing or forward-deployed engineering experience.

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