職務内容：

Job TitleAI Research & Innovation - AI researcherAbout the RoleWe are seeking an experienced Applied AI Research & Engineering Researcher to lead the technical foundation and innovation within our AI division. This leader will be responsible for defining our core ML/AI research agenda, overseeing the development of novel algorithms and models, and driving their robust deployment into production. This is a hands-on technical leadership role for someone who excels at managing a team of researchers and translating complex academic concepts into scalable, reliable enterprise solutions.Responsibilities"Key Responsibilities

• Technical Vision & Research Strategy Set the Technical Roadmap: Define the multi-year research and engineering roadmap for the AI platform, prioritizing projects that solve critical, high-complexity technical challenges (e.g., model efficiency, interpretability, real-time inference). Deep Learning & Modeling: Lead the team in designing, implementing, and optimizing advanced deep learning, generative AI, and reinforcement learning models from scratch, pushing the state-of-the-art for our domain. Academic Translation: Monitor academic research and industry trends to identify and quickly prototype cutting-edge techniques suitable for production deployment.
• MLOps & Production Engineering MLOps Excellence: Establish and enforce best practices for MLOps (Machine Learning Operations), ensuring automation, reproducibility, version control, and continuous integration/continuous delivery (CI/CD) for all models. Architecture Review: Personally review and approve the technical architecture for all deployed AI systems, ensuring they meet strict criteria for scalability, low latency, and fault tolerance. Resource Optimization: Drive research into optimizing computational costs for large models, including strategies for model compression, quantization, and efficient hardware utilization.
• Team Leadership & Technical Mentorship Lead Technical Talent: Recruit, mentor, and manage a high-performing team of Applied AI Scientists, Machine Learning Engineers, and Researchers. Culture of Rigor: Foster a technically demanding and research-driven culture, encouraging publication, patent filing, and open-source contributions. Code Quality: Ensure all core AI codebases adhere to the highest standards of quality, documentation, and maintainability."Qualifications, Skills and Competencies" 15+ years of hands-on experience in Machine Learning, Deep Learning, or AI Research, with a focus on building and deploying complex models. 5+ years of technical leadership experience managing a team of Data Scientists and ML Engineers. Expert-level proficiency in core ML frameworks (e.g., PyTorch, TensorFlow) and data science languages (Python/R). Experience building a commercial practice or product focused on Generative AI and Large Language Models (LLMs). Demonstrated expertise in at least two major AI domains (e.g., Deep Learning, NLP, Computer Vision). Proven track record of success in a client-facing or internal product-focused role, directly translating technical output into commercial results. Deep practical knowledge of MLOps principles and experience with cloud-native ML services (e.g., Google Cloud Vertex AI, SageMaker, Azure ML). Ph.D. or Master's degree in Computer Science, Machine Learning, or a highly quantitative field, OR equivalent demonstrated technical leadership experience.""Technical / Functional Skills:- Preferred Qualifications A strong portfolio of research publications (ICML, NeurIPS, KDD, etc.) or patents related to applied AI. Extensive experience with distributed computing frameworks (Spark, Ray) for large-scale model training and inference. Proven ability to man