Machine Learning Engineer, Robot Learning

<h1><span style="color: rgb(0, 0, 0);">Build the Path Forward</span></h1> <p>At Path Robotics, we’re building the future of embodied intelligence. Our AI-driven systems enable robots to adapt, learn, and perform in the real world closing the skilled labor gap and transforming industries. We go beyond traditional methods, combining perception, reasoning, and control to deliver field-ready AI that is risk-aware, reliable, and continuously improving through real-world use.</p> <p>Big, hard problems are our everyday work, and our team of intelligent, humble, and driven people make the impossible possible together.</p> <p><span style="color: rgb(0, 0, 0);">We are seeking a skilled and motivated Machine Learning Engineer with expertise in modern robotics and manipulation to join our Robot Learning team to build agentic AI systems for industrial applications. The ideal candidate will have experience in robotics, with a focus on developing and implementing advanced manipulation techniques, motion control systems, and planning algorithms for autonomous robots. This role involves working closely with cross-functional teams to design, test, and deploy innovative solutions that improve the performance and capabilities of our robotic systems. </span></p> <h1><span style="color: rgb(0, 0, 0); font-size: 14pt;">What You’ll Do</span></h1> <ul> <li style="color: rgb(0, 0, 0);"><span style="color: rgb(0, 0, 0);">Work on the development and deployment of behavioral cloning (BC), reinforcement learning (RL), and diffusion models to solve complex robotic tasks.</span></li> <li style="color: rgb(0, 0, 0);"><span style="color: rgb(0, 0, 0);">Leverage multi-modal data, including image-based data, force, and torque to enhance robotic manipulation and control.</span></li> <li style="color: rgb(0, 0, 0);"><span style="color: rgb(0, 0, 0);">Design and implement vision-language-action (VLA) models for more intelligent and responsive robotic systems.</span></li> <li style="color: rgb(0, 0, 0);"><span style="color: rgb(0, 0, 0);">Craft strategies for the entire solution's lifecycle, including data collection, fleet learning, and continuous learning.</span></li> <li style="color: rgb(0, 0, 0);"><span style="color: rgb(0, 0, 0);">Develop, optimize, and deploy learning-based methods for robot control and object manipulation algorithms on a fleet of industrial robotic cells.</span></li> <li style="color: rgb(0, 0, 0);"><span style="color: rgb(0, 0, 0);">Collaborate with hardware and software teams to integrate manipulation, control, and planning algorithms into robotic platforms.</span></li&