We are seeking a Senior Applied Scientist with strong hands-on experience in building and optimizing large language models (LLMs), agentic AI systems, and end-to-end model training workflows. This role is ideal for scientists with a solid applied background who can translate state-of-the-art research into real-world impact. A research-oriented mindset with publications in top AI/ML venues is highly preferred but not strictly required. You will collaborate closely with product, engineering, and research teams to ship intelligent, reliable, and innovative AI capabilities at scale.
Responsibilities
- Design and implement advanced LLM-based architectures and agentic systems for real-world product scenarios.
- Lead model training and evaluation efforts, including data preprocessing, fine-tuning, and inference optimization.
- Collaborate across teams to deliver robust, scalable models aligned with product objectives and user value.
- Apply and adapt research ideas to solve practical challenges in reasoning, planning, memory, and alignment.
- Monitor and improve model performance post-deployment through data-driven iteration and error analysis.
- Contribute to technical discussions, model reviews, and best practices within the applied science community.
Qualifications
- M.S. or Ph.D. in Computer Science, Machine Learning, or a related field, or equivalent practical experience.
- 4+ years of experience in applied machine learning, with a focus on LLMs, agent systems, or reinforcement learning.
- Strong hands-on experience with model training pipelines using PyTorch, TensorFlow, JAX, or similar frameworks.
- Familiarity with distributed training, prompt engineering, evaluation strategies, and model deployment best practices.
- Experience with retrieval-augmented generation (RAG), tool use, planning agents, or long-context modeling is a plus.
- Solid publication record (e.g., NeurIPS, ICLR, ACL, ICML, EMNLP) is a plus, but emphasis is placed on practical contributions.
- Strong coding and debugging skills, and comfort working in cross-functional, agile environments.
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.
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