Algorithm Expert

AFRY is a European leader in engineering, design, and advisory services, with a global reach. We accelerate the transition towards a sustainable society.

We are 19,000 devoted experts in infrastructure, industry, energy and digitalisation, creating sustainable solutions for generations to come.

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.

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.