The Applied Scientist II role within the Engineering Operations Data & Applied Sciences team focuses on developing advanced AI solutions to enhance Azure customer experience. This position involves driving AI projects from conception through implementation and ensuring compliance with Microsoft Responsible AI standards. The team values collaboration, working closely with product managers, designers, engineers, and data scientists to deliver impactful results. Candidates will have the opportunity to contribute to cutting-edge GenAI and ML solutions in a dynamic environment.

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field with relevant internship experience, or a Master's Degree in a related field, or equivalent experience.
• Direct experience building intelligent AI Reasoning agents using Machine Learning and language model frameworks with LLMs / SLMs is preferred.

• Drive AI projects through their entire life cycle from idea creation to worldwide availability.
• Perform rigorous experiments and evaluations to assess the quality and impact of solutions and improve them based on data and customer feedback.
• Communicate technical findings and insights effectively.
• Integrate ML models into production systems, monitor and optimize their performance, troubleshoot issues, and iterate on improvements.
• Collaborate with cross-functional teams including researchers, applied scientists, engineers, product managers, and designers.
• Ensure compliance with Microsoft Responsible AI standards throughout the AI system lifecycle.
• Stay abreast of the latest advancements in machine learning, information retrieval, and recommendation systems, and contribute to the company's intellectual property through patents and publications.

• Employees at Microsoft are often offered comprehensive, “world-class” benefits—including health and mental-wellness programs, competitive pay with bonuses and stock awards, and retirement/savings options. Time-off and flexibility are common, with generous vacation and holidays, parental and caregiver leave, and flexible work schedules, alongside learning support, employee resource groups, product discounts, and matching-gifts/volunteering programs. Specific benefits can vary by region.