Staff Computer Vision/Machine Learning Engineer, Perception

Posted 12 Days Ago
Be an Early Applicant
8 Locations
5-7 Years Experience
Artificial Intelligence • Computer Vision • Machine Learning • Robotics • Business Intelligence • Automation • Manufacturing
At Path Robotics, we’re not just solving a manufacturing challenge. We’re solving a recruiting problem.
The Role
Develop and implement algorithms for Robotic Perception tailored for welding tasks, lead R&D initiatives in the welding domain, collaborate with teams to evaluate deep neural networks and machine learning systems, stay updated on Robotics, Computer Vision, and ML research.
Summary Generated by Built In

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 

Top Skills

Python
The Company
HQ: Columbus, OH
220 Employees
On-site Workplace
Year Founded: 2016

What We Do

Path Robotics is an Artificial Intelligence and Robotics company focusing on the manufacturing industry.

Why Work With Us

Distinguishing ourselves from other tech startups, we work with a physical product — the robots. This keeps us rooted in our Columbus, Ohio office and fosters a culture of in person collaboration and ideation.

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