ATI
Lead Perception Engineer
Woburn, United States
Sponsorship not specifiedDetected 72 days ago
PythonC++AlgorithmsCode ReviewMachine LearningDeep LearningPyTorchComputer VisionRoboticsSensorsLeadershipCollaborationProblem SolvingMentoring
About the role
- We are looking for a highly skilled and experienced Lead Perception Engineer with expertise leading a team of engineers solving difficult robotic perception challenges using both classical and machine learning (ML) approaches.
- The ideal candidate will have hands-on experience with developing solutions end to end, including evaluation of the problem, sensor selection, leading software development and evaluating the solution in the real world to ensure success.
Responsibilities
- Lead Technical Execution: Guide a team of engineers through the full development lifecycle, from initial concept, hardware selection and algorithm design to field deployment and maintenance.
- You will lead the team in the following work: Integrate classical and ML image processing algorithms for classification, depth sensing, and 3D reconstruction.
- Create AI and ML models to enhance object detection, classification, and tracking capabilities.
- System Design: Design and maintain high-throughput perception pipelines, ensuring low latency and high reliability in real-time environments.
- Code Quality & Mentorship: Drive high standards for code reviews, architectural design, and documentation while mentoring junior team members.
- Strong foundation in robotics fundamentals, including coordinate transforms, sensor calibration, perception pipeline design, and system architecture.
- Proven ability to perform hands-on, low-level debugging and systematic troubleshooting of complex robotic systems in real-world environments.
- Experience in building ML pipelines and optimizing/productizing ML models.
- Guide a team of engineers through the full development lifecycle, from initial concept, hardware selection and algorithm design to field deployment and maintenance.
- Design and maintain high-throughput perception pipelines, ensuring low latency and high reliability in real-time environments.
Requirements
- At least 2-3 years of experience in a formal or informal leadership capacity, such as a Team Lead, Tech Lead, or Mentor, with a track record of guiding technical projects and junior engineers.
- Expert-level proficiency in Python, C++ and/or Rust with a focus on writing production-grade, well-tested code for autonomous systems.
- At least 2-3 years of experience in a formal or informal leadership capacity, such as a
Benefits
- This role offers an exciting opportunity to work at the forefront of robotics and industrial automation, applying cutting-edge AI and ML techniques to develop advanced vision control systems.
- If you are a perception or computer vision engineer with a passion for solving complex automation challenges, we encourage you to apply and become a key part of our innovative team.
- 8-10 years of professional software engineering experience in robotics, computer vision, or a closely related field.
- Demonstrated experience designing, implementing, testing, and optimizing vision solutions for robotic or automation applications.
- Proficiency in AI/ML frameworks (e.g. PyTorch) and computer vision libraries (e.g., OpenCV, PCL, Open3D, CUDA).
- Familiarity with various depth sensing modalities (e.g., LiDAR, stereo vision, time-of-flight) and sensor fusion.
- Select the optimal sensors (e.g., LIDARs, time-of-flight cameras, stereo vision) for various applications.
- Utilize deep learning techniques to improve system accuracy and efficiency.
Company info
- Integrate classical and ML image processing algorithms for classification, depth sensing, and 3D reconstruction.
- Conduct extensive testing, validation, and calibration to ensure system accuracy and reliability.
- We are transforming a process that hasn't fundamentally changed in decades into an automated, high-performance system built for the future of automotive service.
This listing is sourced directly from ATI's careers page and normalized into a canonical job model.