微软Principal Data & Applied Science Manager
任职要求
Required/Minimum Qualifications: • Undergraduate degree in Computer Science, Engineering, Mathematics, Statistics. • 8+ years development skills in Python, C#, C++ or Java. • 2+ years of people management and/or project management experience. Other Requirements: Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: • Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter. Preferred Qualifications • Masters or PhD degree in Computer Science, Statistics, or related fields (undergraduates with significant appropriate experience will be considered). • Strong academic work and professional experience in statistics, machine learning, including deep learning, NLP, econometrics. • Experience in building cloud-scale systems and experience working with open-source stacks for data processing and data science is desirable. • Experience with LLMs in natural language, AI for code or related fields • Excellent communication skills, ability to present and write reports, strong teamwork and collaboration skills. • Experience in productizing AI and collaborating with multidisciplinary teams. Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations. Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work. #DevDiv Shanghai & DDJL
工作职责
• Initiate and advance research to advance state-of-the-art in AI for Software Engineering • Collaborate across disciplines with product teams across Microsoft and Github • Stay up to date with the research literature and product advances in AI for software engineering • Collaborate with world renowned experts in programming tools and developer tools to integrate AI across software development stack for Copilot • Build and manage large-scale AI experiments and models.
• Technical Architecture Design: Develop and execute system architecture and technical roadmaps to ensure the system's high availability, scalability, and security. • Cross-Team Collaboration: Work closely with product managers, UX designers, data scientists, and other team members to understand business requirements and translate them into technical solutions. • Continuous Improvement and Optimization: Monitor system performance, optimize performance, and troubleshoot issues to ensure stable and efficient system operation. • Technical Innovation: Stay attuned to industry trends and new technologies, actively promoting innovation and the adoption of best practices. • Quality Assurance: Establish and enforce standards for code reviews, unit testing, and integration testing to ensure high code quality and system reliability.
• Research, design, and prototype methods to leverage LLMs for product scenarios such as text understanding, summarization, dialogue, translation, content generation, and reasoning. • Fine-tune, adapt, and optimize pre-trained LLMs for domain-specific tasks while balancing model performance, efficiency, and cost. • Develop scalable pipelines for data collection, cleaning, augmentation, and evaluation. • Collaborate with product and engineering teams to translate applied research into production-quality features. • Define and track key performance metrics for LLM-based features, including accuracy, latency, robustness, and user satisfaction. • Stay current with advances in generative AI, multimodal models, and applied ML techniques, and bring forward innovative ideas to improve our products. • Publish technical insights internally (and externally where appropriate) to advance organizational knowledge and thought leadership.
• Lead the development and evaluation of state-of-the-art models for code completion and editing, pushing the boundaries of code understanding, generation, fix and review. • Develop retrieval-augmented systems that improve a model’s awareness of large and complex codebases, enabling context-rich code assistance. • Design and prototype efficient inference algorithms to enable fast, interactive code generation experiences at scale. • Collaborate across disciplines with product teams across Microsoft and Github • Stay up to date with the research literature and product advances in AI for software engineering
• You will master a broad area or research and understand any applicable research techniques. You’ll also serve as a team expert on changes in industry trends, products, and other advances, and apply this knowledge to influence product needs. • You will review business and product requirement, incorporate research, and provide strategic direction for problem solving. You’ll also ensure scientific rigor, support the development of methods, and apply your expertise to support business impact. • You will identify and inspire peers and new research talent to join Microsoft, build relationships, and advocate for research initiatives. You’ll share research findings through industry outreach, collaborate with the academic community, and help develop the recruiting pipeline. • You will document work and experimentation results and share findings to promote innovation. You’ll provide guidance when capturing processes and contribute to ethics and privacy policies related to research processes and data collection.