ATI
About ATI:
Automated Tire (ATI) is a cutting-edge Series A company focused on revolutionizing the automotive robotics space. The team consists of experienced robotics, industrial automation, and automotive professionals with deep relationships and a distribution network across the U.S. We have strategic backing from long-term capital and the support to build something truly amazing. Come join our team and help us define the future of automotive robotics! 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. Position Overview:
We are looking for a highly skilled and experienced Staff/Principal Perception Engineer with expertise in both classical and machine learning (ML) approaches to solving perception and computer vision challenges related to our robotic system. The ideal candidate will have an in-depth knowledge of object identification, depth estimation, and structure reconstruction. Key Responsibilities:
Design and implement robust, efficient, and well-tested perception algorithms for real-world scenarios. Integrate classical and ML image processing algorithms for classification, depth sensing, and 3D reconstruction. Select optimal sensors (e.g., LIDARs, time-of-flight cameras, stereo vision) for various applications. Create AI and ML models to enhance object detection, classification, and tracking capabilities. Utilize deep learning techniques to improve system accuracy and efficiency. Conduct extensive testing, validation, and calibration to ensure system accuracy and reliability. Collaborate with cross-functional teams, including mechanical, system, mechatronic, software and software quality assurance engineers, and domain experts. Collaborate effectively within the team and communicate clearly, both verbally and in writing. Master’s or PhD degree in Computer Science, Computer Vision, Machine Learning, or a related field. Demonstrated experience designing, implementing, testing, and optimizing vision solutions for robotic or automation applications. Experience working with pixels, low-level statistical features and filter responses, and higher-level representations (feature descriptors, embeddings) Strong programming skills (10+ years of professional experience with Python, Rust, C++ or a similar language) Experience implementing algorithms (statistical, ML, DL) for applications such as object detection, tracking, classification, scene segmentation, or SLAM 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. Excellent problem-solving skills, attention to detail, and ability to work in a dynamic environment. Preferred Qualifications:
Experience with deploying vision systems in real-world robotic solutions. Knowledge of robotic control systems, automation protocols, and communication interfaces. Familiarity with robotic simulation platforms (Issac Sim, Gazebo) to develop robotic systems. Experience developing within the ROS2 ecosystem.
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Automated Tire (ATI) is a cutting-edge Series A company focused on revolutionizing the automotive robotics space. The team consists of experienced robotics, industrial automation, and automotive professionals with deep relationships and a distribution network across the U.S. We have strategic backing from long-term capital and the support to build something truly amazing. Come join our team and help us define the future of automotive robotics! 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. Position Overview:
We are looking for a highly skilled and experienced Staff/Principal Perception Engineer with expertise in both classical and machine learning (ML) approaches to solving perception and computer vision challenges related to our robotic system. The ideal candidate will have an in-depth knowledge of object identification, depth estimation, and structure reconstruction. Key Responsibilities:
Design and implement robust, efficient, and well-tested perception algorithms for real-world scenarios. Integrate classical and ML image processing algorithms for classification, depth sensing, and 3D reconstruction. Select optimal sensors (e.g., LIDARs, time-of-flight cameras, stereo vision) for various applications. Create AI and ML models to enhance object detection, classification, and tracking capabilities. Utilize deep learning techniques to improve system accuracy and efficiency. Conduct extensive testing, validation, and calibration to ensure system accuracy and reliability. Collaborate with cross-functional teams, including mechanical, system, mechatronic, software and software quality assurance engineers, and domain experts. Collaborate effectively within the team and communicate clearly, both verbally and in writing. Master’s or PhD degree in Computer Science, Computer Vision, Machine Learning, or a related field. Demonstrated experience designing, implementing, testing, and optimizing vision solutions for robotic or automation applications. Experience working with pixels, low-level statistical features and filter responses, and higher-level representations (feature descriptors, embeddings) Strong programming skills (10+ years of professional experience with Python, Rust, C++ or a similar language) Experience implementing algorithms (statistical, ML, DL) for applications such as object detection, tracking, classification, scene segmentation, or SLAM 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. Excellent problem-solving skills, attention to detail, and ability to work in a dynamic environment. Preferred Qualifications:
Experience with deploying vision systems in real-world robotic solutions. Knowledge of robotic control systems, automation protocols, and communication interfaces. Familiarity with robotic simulation platforms (Issac Sim, Gazebo) to develop robotic systems. Experience developing within the ROS2 ecosystem.
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