Description
Summary
Microsoft AI are looking for a talented Principal Applied Scientist at their Redmond office. This role sits at the heart of strategic decision-making, transforming complex data into actionable insights for a company that's revolutionising the field of artificial intelligence. You'll work directly with leadership to shape the company's direction in the development of large-scale, Azure-based intelligence platforms.
About the Role
As a Principal Applied Scientist, you will define scientific vision and lead the development of both ML and LLM components. This includes designing robust models, driving experimentation, ensuring statistical rigor, and guiding the platform's evolution toward greater automation, accuracy, and scalability. You will partner closely with engineering and product teams to translate research into reliable production systems, influence long-term strategy, and deliver intelligence that enables smarter, faster, and more informed decisions.
Accountabilities
- Define and drive the modeling strategy for the advertising recommendations platform, spanning classical machine learning (for analytics on structured data) and the use of generative AI.
- Architect end-to-end machine learning pipelines – oversee the design of data processing workflows, feature stores, model training/validation routines, and deployment mechanisms that can reliably produce daily insights for all customers.
The Candidate we're looking for
Experience:
- 6+ years related experience (e.g., statistics, predictive analytics, research) in a field such as statistics, econometrics, computer science, electrical or computer engineering, or a related field.
Technical skills:
- Extensive hands-on expertise in ML techniques for predictive analytics, pattern recognition, and optimization.
- 5+ years of experience with developing and deploying machine learning solutions in production, with proven ownership of complex projects end-to-end (from problem formulation and data acquisition to model deployment and monitoring).
Personal attributes:
- Strong leadership and technical skills, with the ability to mentor and develop the applied science team.
- Excellent communication and collaboration skills, with the ability to work effectively with cross-discipline teams.
Benefits
- Competitive salary and benefits package.
- Opportunities for professional growth and development.
- Collaborative and dynamic work environment.