Senior Applied Scientist

Microsoft • Redmond, WA

19h

About The Position

Joining the CoreAI organization at Microsoft means becoming part of the team that builds the end-to-end AI stack powering Azure’s innovation. As a Senior Applied Scientist on the GenAI Infra and Solutions team within CoreAI, you will help develop the AI infrastructure that accelerates the creation of agentic AI systems across Microsoft. This role is dedicated to advancing scientific methods and scalable infrastructure for training agentic models to achieve frontier-level performance. You will contribute to LLMs, SLMs, and agentic models using both proprietary and open-source frameworks, all aimed at delivering reliable, enterprise-grade agentic workflows.
We are seeking a curious, independent, adaptable problem-solver who thrives on continuous learning, embraces changing priorities, and is motivated by creating meaningful impact. Candidates must be self-driven, able to write efficient code, debug complex training jobs, document findings, and demonstrate a track record in these fields. In addition, we value an agile, startup-style mindset - someone who can iterate quickly, pivot when needed, and collaborate effectively in fast-paced, dynamic environments.
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.
In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Requirements

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research)
• OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
• OR equivalent experience.
• 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.

Nice To Haves

• 2+ years of coding experience in Python and experience with ML frameworks such as PyTorch and Triton
• 2+ years experience of large-scale model training for LLMs, SLMs, and agentic models
• 2+ years of proven ability to design and scale training infrastructure and pipelines in production environments
• Experience with agent training frameworks
• Hands-on experience with large-scale distributed training and/or serving with demonstrated ability to dive deep into complex systems, troubleshoot unconventional issues, and craft innovative solutions under real-world constraints
• Experience with large-scale training, model inference, reinforcement learning, and reasoning models
• Ability to collaborate across interdisciplinary teams and communicate complex ideas clearly
• Startup-style mindset: agile, solution-oriented, and self-driven

Responsibilities

• Write efficient, production-quality code and debug complex training jobs
• Build and maintain training pipelines and architectures across both proprietary and open-source frameworks
• Collaborate effectively within interdisciplinary teams and communicate complex research concepts in clear, actionable ways
• Document findings and insights to enable effective cross-team collaboration and knowledge sharing
• Drive innovations that power flagship Microsoft products and services

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level