Staff AI Engineer (Perception)

• Agility Robotics is deploying humanoid robots that are solving real-world challenges in logistics and manufacturing. Perceiving and understanding the world is critical to Digit’s success in these applications
• The Perception team is looking for a staff machine learning engineer to own the design and development of object detection and tracking algorithms
• As a Staff AI Engineer, you will own the architecture and technical roadmap for object perception systems used by the robot in production
• Design, develop, and deploy machine learning algorithms for multi-object detection, scene understanding, and 6-DoF object pose estimation
• Evaluate and drive adoption of state-of-the-art perception models
• Promote best practices in architecture, design, and testing to deliver high-quality, scalable software
• Optimize deep neural networks and associated data processing to run efficiently on embedded systems
• Collaborate with navigation, manipulation and hardware teams to align perception capabilities with product requirements

Benefits

• A culture that embraces individuality and authenticity
• Employee Referral Bonus Program
• A culture that encourages flexible work schedules
• Relocation Assistance (for certain roles)
• Paid Parental Leave
• Five Weeks of Paid Time Off Annually
• Employer Matched Retirement Plan
• Stock Options (for certain roles)
• 100% Company Paid Disability, Life, Health, Dental & Vision Insurance (for AR employees)- Experience designing and optimizing algorithms for efficient execution across CPU and GPU architectures
• Familiarity with common computer vision and machine learning libraries such as (but not limited to) PyTorch, OpenCV, NumPy, etc
• Strong mathematical fundamentals in linear algebra and numerical optimization and familiarity with core geometric concepts in computer vision
• 5+ years of experience deploying machine learning-based object detection algorithms on mobile robots
• Master’s or Ph.D. in Artificial Intelligence, Robotics, Computer Science, or a related discipline, with a strong foundation in machine learning, robotics, and intelligent systems
• Experience with MLOps such as (but not limited to) data annotation services, data storage, model evaluation tools, and model deployment
• Publications in your field (CVPR, ICCV, RSS, ICRA preferred)
• Proficiency in related technical areas such as (but not limited to) deep convolutional neural networks, multi-object tracking, data association, supervised learning and pose estimation
• Experience developing ML models for 3 or 6 dof pose estimation
• Experience using YOLO, Faster/Mask R-CNN
• Experience in a technical leadership role