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The Data and Artificial Intelligence team in Microsoft’s Developer Division, part of newly formed CoreAI group, is working on the future of AI for Developers! We are a diverse, entrepreneurial and multi-disciplinary group of scientists, researchers and engineers with passion for using AI to improve the productivity of millions of developers around the world. We have released AI for code advancements in Github Copilot, VS Code, Visual Studio and other Microsoft Copilots. We are looking for a passionate and growth-oriented Applied Scientist II to join our team working on high-impact projects at the intersection of AI and software engineering. As an Applied Scientist, you will play a pivotal role in development and application of advanced data science techniques—especially those involving LLMs—to real-world developer workflows. You’ll collaborate closely with data scientists, engineers, researchers, and product teams across Microsoft and GitHub to shape the next generation of AI-powered developer workflows. You will have the opportunity to design and lead experiments, build and evaluate state-of-the-art models (including RAG pipelines, finetuning and evaluation frameworks), turning insights into scalable product features. Most importantly, you’ll play a key role in bridging cutting-edge research and production, using data to inform decisions, drive iteration, and deliver measurable impact at scale.
Job Responsibility:
Research and productization of state-of-the-art in AI for Software Engineering
Build and manage large-scale AI experiments and models
Drive experimentation through A/B testing and offline validation to evaluate model performance
Collaborate across disciplines and geographies with product teams in Microsoft and Github, integrate AI across software development stack for Copilot
Stay up to date with the research literature and product advances in AI for software engineering
Requirements:
Undergraduate degree in Computer Science, Engineering, Mathematics, Statistics
5+ years experience with strong proficiency in Python, machine learning frameworks, and experience developing and deploying generative AI or machine learning models into production
Masters or PhD degree in Computer Science, Statistics, or related fields (undergraduates with significant appropriate experience will be considered)
Strong 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