AI Applied Scientist

We are operating in a period marked by remarkable innovation. As Microsoft advances its leadership in artificial intelligence, we are looking for talented professionals to address some of the most critical and rewarding challenges in the industry. Our objective is to develop a open agentic platform that enables people and organizations to quickly deploy agents and deliver impactful results in real-world scenarios.

We are looking for a principal AI applied scientist to join our Industry agents 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. This role will combine AI knowledge with applied science expertise, and demonstrate a growth mindset and customer empathy. Join us in shaping the future of AI agents for Industries.
You will collaborate across product, research and engineering teams to bring innovative industry solutions to life, applying your expertise in machine learning, data science, and AI to solve complex problems across industries like financial services, government, manufacturing and retail. Your work will directly influence product direction and customer experiences. 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.

• Bachelor’s degree in Computer Science, Statistics, Electrical/Computer Engineering, Physics, Mathematics or related field AND 4+ years of experience in AI/ML, predictive analytics, or research
  
  • OR Master’s degree AND 3+ years of experience
  • OR PhD AND 1+ year of experience
  • OR equivalent experience

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

• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon 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)

• 3+ years of experience publishing in peer-reviewed venues or filing patents

• Experience presenting at conferences or industry events

• 3+ years of experience conducting research in academic or industry settings

• 1+ year of experience developing and deploying live production systems

• 1+ years of experience working with Generative AI models and ML stacks

• Experience across the product lifecycle from ideation to shipping

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 models in transformer-based NLP, prompt engineering, and RAG techniques.
• Fine-tune foundation models using domain-specific datasets. - Evaluate model behavior on relevance, bias, hallucination, and response quality.
• Contribute to papers, patents, and conference presentations. - Translate research into production-ready solutions and measure their impact through A/B testing and telemetry that address customer needs.
• Ability to use data to identify gaps in AI quality, uncover insights and implement PoCs to show proof of concepts.

Leveraging Research in real-world problems

• Demonstrate deep expertise in AI subfields (e.g., deep learning, Generative AI, NLP, muti-modal models) to translate cutting-edge research into practical, real-world solutions that drive product innovation and business impact.
• 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

a deep understanding of fairness and bias in AI by proactively identifying and mitigating ethical and security risks—including XPIA, unfairness, bias, and privacy concerns—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 cycle from data collection to model development, deployment, and monitoring.

Specialty Responsibilities

• Design, develop, and integrate generative AI solutions using large and small language models.
• Deep understanding of small and large language models architecture and optimization techniques to adapt out-of-the-box solutions to particular business problems
• Prepare and analyze data for machine learning, identifying optimal features and addressing data gaps.
• Develop, train, and evaluate machine learning models and algorithms to solve complex business problems, using modern frameworks and state-of-the-art models, open-source libraries, statistical tools, and rigorous metrics
• Address scalability and performance issues using large-scale computing frameworks.
• Monitor model behavior and adapt to changes in data streams.