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Microsoft

AI Applied Scientist

Microsoft, Redmond, Washington, United States, 98052

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Pay found in job post Retrieved from the description.

Base pay range $100,600.00/yr - $215,400.00/yr

We are looking for an AI Applied Scientist 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.

Responsibilities

Bringing the State of the Art to Products

Build collaborative relationships with product and business groups to deliver AI-driven impact

Research and implement state-of-the-art techniques using foundation models, prompt engineering, RAG, graphs, multi-agent architectures, as well as classical machine learning techniques

Fine-tune foundation models using domain-specific datasets

Evaluate model behavior on relevance, bias, hallucination, and response quality via offline evaluations, shadow experiments, online experiments, and ROI analysis

Build rapid AI solution prototypes, contribute to production deployment, debug production code, and support MLOps/AIOps

Contribute to papers, patents, and conference presentations; translate research into production-ready solutions and measure impact through A/B testing and telemetry

Use data to identify gaps in AI quality, uncover insights, and implement PoCs

Leveraging Research in real-world problems

Demonstrate deep expertise in AI subfields (e.g., deep learning, Generative AI, NLP, multi-modal models) to translate research into practical, real-world solutions

Share insights on industry trends and applied technologies with engineering and product teams

Formulate strategic plans that integrate state-of-the-art research to meet business goals

Documentation

Maintain clear documentation of experiments, results, and methodologies

Share findings through internal forums, newsletters, and demos to promote innovation and knowledge sharing

Ethics, Privacy and Security

Apply a deep understanding of fairness and bias in AI; identify and mitigate ethical and security risks to ensure equitable and responsible outcomes

Ensure responsible AI practices throughout the development lifecycle, from data collection to deployment and monitoring

Contribute to internal ethics and privacy policies and ensure responsible AI practice throughout AI development lifecycle

Specialty Responsibilities

Design, develop, and integrate generative AI solutions using foundation models

Understand language model architectures, deep learning, fine-tuning techniques, multi-agent architectures, classical ML, and optimization to adapt solutions to business problems

Prepare and analyze data for machine learning, identify features, and address data gaps

Develop, train, and evaluate ML models and algorithms using modern frameworks and rigorous metrics

Address scalability and performance issues using large-scale computing frameworks

Monitor model behavior, guide product monitoring and alerting, and adapt to changing data streams

Qualifications Required Qualifications

Bachelor’s degree in computer science, Statistics, Electrical/Computer Engineering, Physics, Mathematics or related field AND 2+ years of experience in AI/ML, predictive analytics, or research

OR Master’s degree AND 2+ years of experience

OR equivalent experience

1+ years of experience with generative AI OR LLM/ML algorithms

Other Requirements

Ability to meet Microsoft, customer and/or government security screening requirements

Microsoft Cloud Background Check: must pass at hire/transfer and every two years thereafter

Preferred Qualifications

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 in one or more of the following: C#, Java, React/Angular, TypeScript

Experience with enterprise-scale services design and implementation

1+ years of publishing in peer-reviewed venues or filing patents

Experience presenting at conferences or industry events

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

1+ years of experience contributing to model finetuning pipelines (e.g., LoRA, domain/task-specific adaptation)

Pay and location Applied Sciences IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 per year. There is a different range for specific work locations within the San Francisco Bay area and New York City metro area, with base pay range USD $131,400 - $215,400 in those locations.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

Application window Microsoft will accept applications for the role until November 11, 2025.

EEO 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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