智驾模型算法工程师-规划/预测

该职位来源于猎聘 About the Role As Scania accelerates its "Next Era" transformation, our Shanghai R&D center is pioneering the shift from traditional modular pipelines to cutting-edge End-to-End (E2E) deep learning architectures. We are seeking a highly skilled and innovative Algorithm Expert to lead the core algorithm research and development of our adavanced algorithm developing. You will be at the forefront of designing state-of-the-art neural networks that translate raw sensor data into safe, human-like driving actions tailored for the complex Chinese market. Key Responsibilities

• End-to-End Model Design & Innovation: Lead the architecture design, implementation, and optimization of next-generation End-to-End autonomous driving models, covering the full stack from perception, prediction, decision-making, to planning.
• Generative AI Exploration: Develop and implement E2E algorithm solutions based on cutting-edge generative technologies, including VLM/VLA (Vision-Language/Action Models), LLMs (Large Language Models), and Diffusion Models.
• Inference Optimization & Deployment: Spearhead model inference acceleration and performance optimization. Drive model lightweighting strategies for embedded platforms to resolve high latency and compute bottlenecks in real-world applications.
• Data Engine & Evaluation: Participate in the development of automated data pipelines and establish robust model evaluation metrics. Continuously iterate and enhance E2E model performance through closed-loop data mining.
• Cross-functional Collaboration: Collaborate closely with system architects and embedded engineering teams to ensure seamless model integration and deployment. Solve practical performance issues and continuously improve model effectiveness in actual road tests.
• Frontier Tech Research: Stay at the bleeding edge of large-scale models and reinforcement learning (RL). Explore the migration and application of these advanced technologies within commercial vehicle driving scenarios. Qualifications & Requirements
• Education: Master’s degree or PhD in Computer Science, Artificial Intelligence, Information Engineering, Electronic Engineering, Robotics, or a related field.
• Experience:
• 3+ years of hands-on experience in deep learning algorithm development, preferably within the autonomous driving or robotics industry.
• A strong publication record in top-tier AI/CV conferences (CVPR, ICCV, NeurIPS, etc.) or proven success in relevant open-source projects is highly preferred.
• Technical Expertise:
• Proficient in Python and C++, with extensive practical experience in deep learning frameworks such as PyTorch or TensorFlow.
• Deep understanding of mainstream algorithms in perception, prediction, and planning/control.
• Solid grasp of Imitation Learning (IL) and Reinforcement Learning (RL) principles.
• Strong experience in model inference optimization, including model compression techniques (pruning, distillation) and quantization (INT8/FP16). Familiarity with high-performance inference frameworks like TensorRT, ONNX Runtime, or vLLM is highly desirable.
• Problem Solving: Excellent logical thinking, systematic problem-solving abilities, and strong fundamentals in data structures and algorithms. Passionate about autonomous driving technology and eager to tackle challenging real-world engineering problems.
• Communication: Fluent in English and Mandarin, capable of effectively collaborating with global HQ and local cross-functional teams.