Applied Scientist

Microsoft • Redmond, WA

1d

About The Position

As Applied Scientist II - AI for The Customer Service Applications Team, you will play a pivotal role in advancing Microsoft's mission to empower every individual and organization on the planet to achieve more. You will contribute to the development and integration of cutting-edge AI technologies into Microsoft products and services, ensuring they are inclusive, ethical, and impactful. You will collaborate across product, research and engineering teams to bring innovative solutions to life, applying your expertise in machine learning, data science, and AI to solve complex problems. Your work will directly influence product direction and customer experience. Microsoft is driving innovation and openness in AI, aiming to build an open architecture platform where users can deploy customized AI agents for real-world impact. The role seeks individuals with both AI and applied science expertise, a growth mindset, and strong customer empathy to help address significant challenges and shape the future of AI solutions. 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.

Requirements

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ 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 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
• 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

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ 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+ year(s) 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.
• 1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers).
• 1+ years of experience publishing in peer-reviewed venues or filing patents.
• 1+ years of experience conducting research in academic or industry settings.
• 1+ years of experience working with Generative AI models and ML stacks.
• Experience across the product lifecycle from ideation to shipping.
• Experience with MLOps Workflows, including CI/CD, monitoring, and retraining pipelines.
• Familiarity with modern LLMOps frameworks (e.g., LangChain, PromptFlow).
• Experience developing and deploying live production systems one or more of the following: C#, Java, React/Angular, TypeScript.
• Experience presenting at conferences or industry events.
• Experience with design and implementation of enterprise-scale services.
• 1+ years of experience with generative AI OR LLM/ML algorithms.

Responsibilities

• Collaborate with product and business teams to deliver impactful AI solutions using advanced techniques like foundation models, prompt engineering, and multi-solution architectures.
• Fine-tune AI models with domain-specific data, evaluate and monitor their performance, and rapidly prototype and deploy AI systems.
• Support MLOps by translating research into production-ready applications, maintaining clear documentation, and sharing insights.
• Proactively address ethical, privacy, and security risks to ensure responsible AI development throughout the lifecycle.
• Design, develop, and integrate generative AI solutions using deep understanding of language models, deep learning, and optimization techniques to solve business problems.
• Prepare and analyze data for machine learning, identify optimal features, and address data gaps using modern frameworks and state-of-the-art models.
• Ensure scalability and performance of AI solutions, continuously monitor model behavior, and adapt to evolving data streams.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees