New 
Senior Applied Scientist
 Microsoft | |
 United States, Washington, Seattle | |
 Oct 08, 2025 | |
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OverviewThe Microsoft Applied Sciences Group incubates disruptive technologies for Microsoft's next-gen hardware products and is working on several exciting projects that will shape how computers and other devices perceive the user and the user's environment. Operating as a startup within the company, this team works closely with several research and product teams to bring compelling new experiences to the market. A lot of these experiences are powered by machine learning - and as part of this team, you will have the unique opportunity to work on almost every aspect of a machine learning project - from ideation to shipping. You will have the opportunity to turn ideas into reality with real-world impact at Microsoft scale.As an Senior Applied Scientist you will have the opportunity to design and lead the implementation of state-of-the-art language and multimodal models to transform the Windows experience. You will have the opportunity to collaborate with people at the forefront of their field from across the organization and see your ideas turn ideas into reality with real-world impact at Microsoft scale. This is a hands-on role.Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
ResponsibilitiesResearch focusing on foundation models - Designing and training language and multimodal models (and finetunes) with supervised finetuning, distillation, reinforcement learning, low-rank adaptation.Research focusing on environment interaction, policy specification and verification and human intent alignment.Implementation: Train, distill, and finetune language and vision models in PyTorch, DeepSpeed, AzureML stack.Machine learning engineering - Build pipelines to test designs, algorithms and models.Data science - Research and develop synthetic data generation strategies.Proactively follow state of the art research and share latest work, write papers, attend conferences and share knowledge in the wider team. | |