Applied Scientist II

The Purview AI Classification team builds advanced AI capabilities to identify and classify sensitive information at enterprise scale with a strong focus on Named Entity Recognition (NER) and rigorous AI evaluation. We develop and improve ML/NLP models for complex entity recognition scenarios and build evaluation methodologies to systematically measure accuracy precision recall robustness and model improvements across diverse datasets and real-world conditions. The Applied Scientist will drive experimentation dataset and error analysis model evaluation and iterative improvements to NER and classification quality while partnering closely with engineering and product teams to translate scientific advances into scalable capabilities within Microsoft Purview.

Microsofts 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.

• Design develop and deploy AI/ML systems end-to-end covering data ingestion feature engineering model training evaluation and production integration.
• Build and optimize Generative AI and LLM-based systems including agentic workflows prompt engineering RAG and fine-tuning.
• Write production-grade code in Python C# etc. with emphasis on scalability performance security testability and maintainability.
• Partner with engineering product management and applied science teams to translate customer/business requirements into robust technical solutions.
• Ship and operate large-scale AI services in the cloud owning reliability latency throughput accuracy and cost efficiency.
• Define and execute model evaluation strategies including offline experimentation online monitoring drift detection bias analysis and feedback loops.
• Implement MLOps practices including model CI/CD versioning rollout strategies observability and live-site monitoring. -
• Apply Responsible AI principles covering privacy security explainability fairness and compliance throughout development and deployment.
• Stay current with advances in GenAI LLM frameworks and ML infrastructure and evaluate their applicability to enterprise security scenarios.
  
  

• Bachelors degree in Computer Science Data Science Engineering or a related technical field.
• 5 years overall experience including hands-on model development experience and writing production-quality code
• Solid understanding of ML fundamentals model evaluation experimentation and performance trade-offs.
• Experience building or operationalizing LLM / Generative AI systems including RAG prompt engineering or agent-based architectures.
• Ability to collaborate across disciplines and operate autonomously at senior IC scope.
  
  

This position will be open for a minimum of 5 days with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. 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 with religious accommodations and/or a reasonable accommodation due to a disability during the application process read more about requesting accommodations.

Required Experience:

IC