Principal Applied Science Manager
Job Description
As a Principal Applied Science Manager for BIC (Business Industry Copilots) Agent Cloud, 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 experiences. 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. 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.
Locations
- Redmond, Washington, United States, Redmond, Washington, United States
Salary
Salary not disclosed
Required Qualifications
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ 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 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research) (degree)
- OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) (degree)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research) (degree)
- OR equivalent experience. (degree)
- 3+ years of people management experience. (degree)
- 1+ years of experience with generative AI OR LLM/ML algorithms (degree)
- 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: (degree)
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter. (degree)
- Experience with MLOps Workflows, including CI/CD, monitoring, and retraining pipelines. (degree)
- Familiarity with modern LLMOps frameworks (e.g., LangChain, PromptFlow) (degree)
- 5+ years of experience publishing in peer-reviewed venues or filing patents (degree)
- Experience presenting at conferences or industry events (degree)
- 5+ years of experience conducting research in academic or industry settings (degree)
- 3+ year of experience developing and deploying live production systems (degree)
- 3+ years of experience working with Generative AI models and ML stacks (degree)
Responsibilities
- Build collaborative relationships with product and business groups to deliver AI-driven impact
- Lead Research and implementation of state-of-the-art 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 of these solutions, debug production code, support MLOps/AIOps.
- Contribute to papers, patents, and conference presentations.
- 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.
- Maintain clear documentation of experiments, results, and methodologies.
- Share findings through internal forums, newsletters, and demos to promote innovation and knowledge sharing
- 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.
- Design, develop, and integrate generative AI solutions using foundation models and more.
- Deep understanding of small and large language models architecture, Deep learning, fine tuning techniques, multi-agent architectures, classical ML, 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.
Travel Requirements
3 days / week in-office
