Principal Applied Scientist

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.

**Responsibilities**:

- Model Development & Deployment: Build and optimize ML/DL models using frameworks like PyTorch or TensorFlow. Contribute to the deployment of models in production environments, ensuring scalability and performance.
- Cross-Functional Collaboration: Work closely with engineering, product, and research teams to define goals, align on priorities, and deliver impactful features. Translate business needs into technical solutions.
- Experimentation & Evaluation: Conduct experiments to evaluate model performance, analyze results, and iterate on solutions. Use data-driven insights to improve precision, recall, and user satisfaction.
- Innovation & Impact: Explore new signals, data sources, and modeling techniques to enhance intelligent systems. Contribute to the evolution of the Copilot ecosystem and agentic experiences in Office.

**Qualifications**:
**Required Qualifications**:

- Bachelor'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 Master'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 Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
- 6+ years of industry experience in applied machine learning or data science roles.
- Proficiency in Python and ML libraries (e.g., PyTorch, TensorFlow). Experience with NLP, generative models, or content understanding is highly desirable.
- Demonstrated ability to tackle open-ended problems and deliver practical, scalable solutions.
- Solid written and verbal communication skills. Ability to explain complex technical concepts to non-technical stakeholders.

**Preferred Qualifications**:

- Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
- 5+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers).
- Hands-on experience with modern LLM evaluation techniques, including LLM-as-a-Judge, agentic evaluations, and RAG assessments.
- 3+ years experience developing and deploying large language models (LLMs), including agentic systems, supervised fine-tuning, and Reinforcement Learning (RLHF)
- 3+ years experience designing, implementing, and optimizing Retrieval-Augmented Generation (RAG) pipelines and advanced context engineering.
- Experience contributing to research publications, patents, or open-source projects.
- Hands-on experience deploying ML models in production environments.
- Familiarity with the full product lifecycle, from ideation to deployment and iteration.