**Company Introduction** At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a start-up and the wisdom of seasoned experts, Bot Auto boasts a team that has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create miracles and propel the future of transportation. Join us and transform your dreams into reality. ### Key Responsibilities - **Model Implementation & Iteration:** Participate in the development, training, and optimization of state-of-the-art deep learning models for autonomous driving, with a focus on end-to-end architectures, including object detection, tracking, online mapping, and end-to-end planning. - **Full Lifecycle Execution:** Engage in the entire machine learning workflow under the guidance of domain experts, spanning from data curation and data analysis to model experimentation, hyperparameter tuning, and rigorous performance metric verification. - **Cross-Functional Collaboration:** Partner with simulation, infrastructure, and downstream planning/control teams to deploy, evaluate, and integrate machine learning components into our production pipeline for autonomous trucks. - **Literature Tracking:** Stay abreast of the latest research breakthroughs in computer vision and generative AI, and actively bench-test promising SOTA methods to solve real-world corner cases. ### Qualifications ### Required: - **Education:** An advanced degree (Master’s or Ph.D., including upcoming graduates) in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, Physics, or a related quantitative field. - **Core Knowledge:** Strong theoretical foundation in machine learning, deep learning, and computer vision, with a solid understanding of modern architectures (e.g., Transformers, CNNs, Graphs). - **Technical Stack:** Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow, along with strong software engineering fundamentals (data structures, algorithms, and clean coding practices). - **Attributes:** High self-motivation, strong analytical and problem-solving skills, a fast learner in a high-velocity startup environment, and a strong team-player mindset. ### Preferred (Targeted Research & Background): - **Specific Research Directions**: Academic thesis or deeply focused research experience in one or more of the following domains: - 3D Computer Vision / Bird’s-Eye-View (BEV) Perception - Online Mapping, Vectorization, or Visual SLAM - Prediction and Behavioral Modeling - **Academic Achievements**: A proven track record of research publications in top-tier machine learning, computer vision, or robotics conferences/journals (e.g., CVPR, ICCV, ECCV, NeurIPS, ICLR, ICRA, IROS) as a primary contributor. - **Engineering Plus**: Hands-on experience with model deployment, quantization, distillation, or inference acceleration tools (e.g., TensorRT, ONNX, CUDA, C++). - **Industry Exposure**: Prior internship experience within the autonomous driving industry or advanced robotics labs is highly desirable.