Staff Machine Learning Engineer, Perception
Build the Path Forward
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.
Big, hard problems are our everyday work, and our team of intelligent, humble, and driven people make the impossible possible together.
We're seeking a passionate individual to join our team at the intersection of welding science and artificial intelligence. As a Staff Machine Learning Engineer, you'll be instrumental in developing robotic welding solutions. You'll use your skills in computer vision, deep learning, and Python programming to tackle challenges in our field alongside our talented teams.
What You’ll Do
- Lead the development and implementation of advanced algorithms for robotic perception systems tailored to industrial welding tasks, integrating data from diverse vision sensors such as RGB/GigE, LiDAR, and ToF depth sensors.
- Oversee research initiatives to address complex welding-related challenges, utilizing image processing, point cloud data, and 3D sensor fusion, contributing to innovative solutions for domain-specific problems.
- Collaborate with multidisciplinary teams to design and lead experiments evaluating state-of-the-art deep learning models, optimizing machine learning systems for robotic perception in welding.
- Stay at the forefront of advancements in Robotics, Computer Vision, and ML research, driving the integration of cutting-edge technologies into real-world applications, and ensuring these innovations have a high impact on production systems.
- Mentor and guide junior engineers, providing technical leadership and fostering collaboration to enhance team expertise in perception systems and machine learning.
- Contribute to strategic decisions about system architecture and the direction of robotics perception technologies within the company, ensuring alignment with product and business goals.
Who You Are
- Master’s or Ph.D. in Computer Science, Robotics, or a related field with a focus on Computer Vision, Machine Learning, or Perception Systems.
- 5+ years of experience in developing machine learning algorithms or applications for real-world robotics systems, particularly in industrial or manufacturing environments.
- Strong proficiency in Python, as well as experience with other relevant languages (e.g., C++), and a deep understanding of neural networks, deep learning architectures, and 3D data processing.
- Extensive experience with vision sensors (e.g., RGB, LiDAR, ToF) and demonstrated ability to apply sensor fusion techniques for perception tasks.
- A proven track record of leading projects and research initiatives, with the ability to bridge the gap between theoretical research and practical, deployable solutions.
- Enthusiastic about working in a fast-paced, dynamic startup environment, with the ability to influence company-wide technological direction and strategy.
Why You’ll Love Working Here
- Daily free lunch to keep you fueled and connected with the team
- Flexible PTO so you can take the time you need, when you need it
- Comprehensive medical, dental, and vision coverage
- 6 weeks fully paid parental leave, plus an additional 6–8 weeks for birthing parents (12–14 weeks total)
- 401(k) retirement plan through Empower
- Generous employee referral bonuses—help us grow our team!
Who We Are
At Path Robotics we love coming to work to solve interesting and tough challenges but also because our ideas are welcomed and valued. We encourage unique thinking and are dedicated to creating a diverse and inclusive environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.