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Why Join UsAt Bot Auto, you’ll work on cutting-edge autonomous technologies that directly impact how self-driving cars perceive and navigate the world.
You’ll collaborate with experts across AI, mapping, and robotics, shaping the next generation of intelligent mapping systems. About the RoleWe are seeking a highly motivated Machine Learning Engineer to join our HD mapping team.
The ideal candidate will develop learning-based algorithms for online map building in both well-maintained road environments and challenging construction zones.
You will leverage cutting-edge deep learning and transformer-based architectures to improve our real-time mapping and perception systems, which serve as the foundation for safe and scalable autonomous driving. Key ResponsibilitiesDesign, train, and deploy deep learning models for lane marking and road feature detection using camera, LiDAR, and other sensor data. Develop transformer-based architectures and leverage other modern deep learning techniques for spatial-temporal perception and HD map updating. Handle complex scenarios such as poorly painted lanes and temporary construction areas in dynamic weather conditions. Collaborate with perception, localization, and planning teams to integrate learning-based map components into the autonomous driving system. Conduct data analysis, dataset curation, and annotation for model training and evaluation.
Qualifications
RequiredHave an advanced degree (Ph. D or Master’s) in related fields of study: computer science, computer engineering, robotics, mathematics, and etc.
In-depth knowledge and extensive experience in deep learning, computer vision, and modern transformer architectures. Hands-on experience with ML frameworks such as PyTorch or TensorFlow. Solid programming skills in Python and preferably C++. Strong problem-solving skills and ability to work in a fast-paced, research-driven environment. PreferredHave a proven track record of research publications in top machine learning conferences and/or journals. Prior experience in autonomous driving perception, semantic segmentation, online map generation, or multi-modal sensor fusion is highly desirable. Experience with real-world deployment of perception models in robotics or autonomous systems. Background in handling large-scale datasets and real-time processing pipelines.
You’ll collaborate with experts across AI, mapping, and robotics, shaping the next generation of intelligent mapping systems. About the RoleWe are seeking a highly motivated Machine Learning Engineer to join our HD mapping team.
The ideal candidate will develop learning-based algorithms for online map building in both well-maintained road environments and challenging construction zones.
You will leverage cutting-edge deep learning and transformer-based architectures to improve our real-time mapping and perception systems, which serve as the foundation for safe and scalable autonomous driving. Key ResponsibilitiesDesign, train, and deploy deep learning models for lane marking and road feature detection using camera, LiDAR, and other sensor data. Develop transformer-based architectures and leverage other modern deep learning techniques for spatial-temporal perception and HD map updating. Handle complex scenarios such as poorly painted lanes and temporary construction areas in dynamic weather conditions. Collaborate with perception, localization, and planning teams to integrate learning-based map components into the autonomous driving system. Conduct data analysis, dataset curation, and annotation for model training and evaluation.
Qualifications
RequiredHave an advanced degree (Ph. D or Master’s) in related fields of study: computer science, computer engineering, robotics, mathematics, and etc.
In-depth knowledge and extensive experience in deep learning, computer vision, and modern transformer architectures. Hands-on experience with ML frameworks such as PyTorch or TensorFlow. Solid programming skills in Python and preferably C++. Strong problem-solving skills and ability to work in a fast-paced, research-driven environment. PreferredHave a proven track record of research publications in top machine learning conferences and/or journals. Prior experience in autonomous driving perception, semantic segmentation, online map generation, or multi-modal sensor fusion is highly desirable. Experience with real-world deployment of perception models in robotics or autonomous systems. Background in handling large-scale datasets and real-time processing pipelines.
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Bot Auto United States
