Staff Computer Vision/Machine Learning Engineer | Path Robotics | Remote (United States)
Build the Path Forward
At Path Robotics, we’re attacking a trillion dollar opportunity – doing things that have never been done before to support an industry hurting from a lack of skilled labor. Big, hard problems are what Path tackles every day and our people are our greatest asset to get that job done. Our intelligent, hardworking team of people do the impossible every single day, yet remain incredibly kind, humble, and always ready to support one another.
We’re on the lookout for an outstanding individual to play a crucial role in the intersection of welding science and artificial intelligence. As a Staff Computer Vision/Machine Learning Engineer, you’ll apply your expertise in computer vision, deep learning, machine learning, surface reconstruction, sensor fusion, and Python programming to create robotic welding solutions. This combination will be pivotal in driving innovation to tackle intricate challenges in our field. Collaborating closely with our exceptional AI, robotics, weld science, and software engineering teams you’ll be at the forefront of developing groundbreaking AI-driven robotic welding methods.
What You’ll Do
• Develop and implement algorithms for Robotic Perception specifically tailored for welding tasks, including integration, calibration, and fusion of vision sensors such as RGB/GigE, LiDAR, ToF depth sensors, Kinect, RGB-D, and Fish-eye cameras.
• Leading R&D initiatives aimed at addressing challenges related to novel problems in the welding domain, using multi-modal image and point cloud data as input, and solving unique domain specific welding problems
• Collaborate with cross-functional teams to design and execute experiments to evaluate the efficacy of deep neural networks and machine learning systems, encompassing processes, parameters, algorithms, and equipment, with a focus on deep learning
• Stay updated on the latest advancements in Robotics, Computer Vision, and ML research, and integrate relevant technologies into autonomous welding robot developments.
Who you are
• PhD or MS in Computer Science with a focus on Computer Vision and Machine Learning, or equivalent practical experience/education, with a strong foundation in neural networks and data driven models.
• Over 5 years of experience dedicated to pioneering novel machine learning algorithms/applications, including more than 3 years of industry exposure to designing, developing, and deploying real-world deep neural network models using Python.
• Have a strong understanding and demonstration of test driven coding standards with experience in deploying production code.
• Enthusiastic about joining a venture-backed start-up company, recognizing the immediate and direct influence your work will have.
Best way to stand out
• Proven track record in publishing at top conferences (e.g. CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML)
• Experience with computer graphics and surface reconstruction
• Open-source contributions related to multimodal ML models
• C++ and ROS experience
Apply tot his job
Apply To this Job
At Path Robotics, we’re attacking a trillion dollar opportunity – doing things that have never been done before to support an industry hurting from a lack of skilled labor. Big, hard problems are what Path tackles every day and our people are our greatest asset to get that job done. Our intelligent, hardworking team of people do the impossible every single day, yet remain incredibly kind, humble, and always ready to support one another.
We’re on the lookout for an outstanding individual to play a crucial role in the intersection of welding science and artificial intelligence. As a Staff Computer Vision/Machine Learning Engineer, you’ll apply your expertise in computer vision, deep learning, machine learning, surface reconstruction, sensor fusion, and Python programming to create robotic welding solutions. This combination will be pivotal in driving innovation to tackle intricate challenges in our field. Collaborating closely with our exceptional AI, robotics, weld science, and software engineering teams you’ll be at the forefront of developing groundbreaking AI-driven robotic welding methods.
What You’ll Do
• Develop and implement algorithms for Robotic Perception specifically tailored for welding tasks, including integration, calibration, and fusion of vision sensors such as RGB/GigE, LiDAR, ToF depth sensors, Kinect, RGB-D, and Fish-eye cameras.
• Leading R&D initiatives aimed at addressing challenges related to novel problems in the welding domain, using multi-modal image and point cloud data as input, and solving unique domain specific welding problems
• Collaborate with cross-functional teams to design and execute experiments to evaluate the efficacy of deep neural networks and machine learning systems, encompassing processes, parameters, algorithms, and equipment, with a focus on deep learning
• Stay updated on the latest advancements in Robotics, Computer Vision, and ML research, and integrate relevant technologies into autonomous welding robot developments.
Who you are
• PhD or MS in Computer Science with a focus on Computer Vision and Machine Learning, or equivalent practical experience/education, with a strong foundation in neural networks and data driven models.
• Over 5 years of experience dedicated to pioneering novel machine learning algorithms/applications, including more than 3 years of industry exposure to designing, developing, and deploying real-world deep neural network models using Python.
• Have a strong understanding and demonstration of test driven coding standards with experience in deploying production code.
• Enthusiastic about joining a venture-backed start-up company, recognizing the immediate and direct influence your work will have.
Best way to stand out
• Proven track record in publishing at top conferences (e.g. CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML)
• Experience with computer graphics and surface reconstruction
• Open-source contributions related to multimodal ML models
• C++ and ROS experience
Apply tot his job
Apply To this Job