Advancing artificial intelligence, machine learning, and model optimization in the context of Microsoft 365's core services to power intelligent features across the M365 ecosystem.
Requirements
- 1+ years of experience training/fine tuning AI/ML models, preferably LLMs/SLMs (small language model).
- 1+ years' experience with productization or shipping ML and/or AI components at internet scale.
- 1+ year(s) experience creating publications such as patents or peer-reviewed academic papers
- 4+ years of experience with end-to-end in a challenging technical problem domain (plan, design, execution, continuous release, and service operation).
- 2+ years of experience building Generative AI pipelines, e.g. with RAG (Retrieval augmented generation).
Responsibilities
- Conduct research and development to push the boundaries of model training, evaluation, and quality assessment for AI solutions.
- Post-train LLMs for enterprise scenarios M365 Copilot and on tenant data to enable task-specific agents and solutions within the enterprise ecosystem
- Collaborate with engineers and researchers to advance deep learning, natural language processing (NLP), multimodal models, and model optimization techniques.
- Measure, analyze, and report on model performance, quality, and impact using predictive analytics and statistical methodologies.
- Contribute to a culture of inclusion, respect, integrity, and accountability while fostering innovation and growth across teams.
Other
- Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
- Contribute to a culture of inclusion, respect, integrity, and accountability while fostering innovation and growth across teams.
