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Path Robotics is building embodied AI systems that enable robots to adapt, learn, and perform in real-world environments, addressing the skilled labor gap across industries. The company combines perception, reasoning, and control to deliver field-ready AI solutions that are risk-aware, reliable, and continuously improving.
As a Staff Machine Learning Engineer focused on Perception, you will lead the development of advanced algorithms for robotic perception systems tailored to industrial welding applications. Your work will span computer vision, deep learning, and sensor fusion across diverse vision sensors including RGB/GigE cameras, LiDAR, and Time-of-Flight depth sensors.
Key responsibilities include:
- Leading development and implementation of perception algorithms for robotic welding systems, integrating data from multiple sensor types
- Overseeing research initiatives to solve complex welding-related challenges using image processing, point cloud analysis, and 3D sensor fusion
- Designing and leading experiments to evaluate state-of-the-art deep learning models, optimizing ML systems for robotic perception
- Staying current with advances in robotics, computer vision, and ML research, driving integration of cutting-edge technologies into production systems
- Mentoring junior engineers and providing technical leadership on perception systems and machine learning
- Contributing to strategic decisions on system architecture and the direction of robotics perception technologies
You bring a Master's or Ph.D. in Computer Science, Robotics, or related field with focus on Computer Vision, Machine Learning, or Perception Systems. You have 5+ years developing ML algorithms for real-world robotics systems, particularly in industrial or manufacturing environments. Strong proficiency in Python and experience with C++ or similar languages is essential, along with deep understanding of neural networks, deep learning architectures, and 3D data processing. You have extensive hands-on experience with vision sensors and sensor fusion techniques, a proven track record leading projects and research initiatives, and the ability to bridge theoretical research with deployable solutions. You thrive in fast-paced startup environments and can influence company-wide technological direction.
