Applied Scientist

Microsoft•Redmond, WA

About The Position

Are you a customer-obsessed, AI-curious problem-solver who thrives in an inclusive, collaborative global team? Join Engineering Operations (EngOps) – the organization driving operational excellence across the Microsoft Cloud to strengthen quality, reliability, security, and customer trust. As part of EngOps, you’ll design solutions that prevent issues before they happen, embed AI-powered automation, and turn signals into actions that deliver measurable customer impact. Our culture of empowerment, inclusion, and growth mindset defines how we work. Every day, customers stake their business and reputation on our cloud. You can help EngOps keep them secure, resilient, and ready. In the new era of AI, this role within Engs Ops Data & Applied Sciences team will provide you the opportunity to work on cutting-edge GenAI and ML (Machine Learning) solutions that drive specific, measurable, and impactful improvements to key areas of Azure customer experience. In an environment of high opportunity and impact, we are looking for an Applied Scientist II who can deliver on key initiatives for Security, Reliability and Quality through advanced AI solutions with a cross-functional team of Product Managers, Designers, Engineers and Data Scientists.

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND relevant internship experience (e.g., statistics, predictive analytics, research)
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
OR equivalent experience.

Nice To Haves

Direct experience building intelligent AI Reasoning agents using Machine Learning and language model frameworks with LLMs / SLMs

Responsibilities

Drive AI projects through their entire life cycle from idea creation through applied research, implementation, experimentation and finally to worldwide availability.
Perform rigorous experiments and evaluations to assess the quality and impact of your 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 to 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.