We are seeking a highly accomplished Principal Applied Scientist with deep expertise in large language models (LLMs)—including both text and multimodal systems—reinforcement learning, agentic AI architectures, and large-scale model training and inference optimization. This is a senior individual contributor role for a thought leader who brings together cutting-edge research excellence and strong applied instincts. You will operate at the frontier of AI science and product innovation, driving the design and deployment of next-generation AI systems at scale. A strong publication record in top-tier AI and machine learning conferences or journals is required. **Responsibilities** • Lead the design and development of advanced AI models and agentic systems for real-world applications. • Own and drive end-to-end model training, including data pipeline design, distributed training optimization, and performance evaluation. • Translate research breakthroughs into production-ready algorithms, contributing to core capabilities such as reasoning, planning, and long-term memory. • Collaborate closely with engineering, product, and research teams to align scientific innovations with product strategy and roadmap. • Mentor junior scientists and provide technical leadership across high-impact projects. • Contribute to the organization’s scientific direction by identifying research opportunities that drive long-term differentiation. **Qualifications** • Ph.D. (or equivalent research experience) in Computer Science, Machine Learning, Artificial Intelligence, or a related field. • 6+ years of experience in AI/ML, with a focus on LLMs, reinforcement learning, or agentic AI systems. • Strong publication record in top-tier conferences/journals such as NeurIPS, ICML, ICLR, ACL, CVPR, TPAMI, or JMLR. • Expertise in neural network architectures, self-supervised learning, model alignment, and evaluation methodologies. • Experience with large-scale distributed training, model optimization, and deployment infrastructure. • Familiarity with advanced techniques such as retrieval-augmented generation (RAG), model compression, or online/continual learning is a plus. • Strong coding and prototyping skills (e.g., PyTorch, JAX, TensorFlow) and ability to collaborate with engineering teams on productization. • Excellent communication and leadership skills in a cross-functional, fast-paced environment. 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 (https://careers.microsoft.com/v2/global/en/accessibility.html) .