OverviewWe are looking for a
Senior Applied Scientist to develop and ship machine learning innovations across the Windows AI stack. In this role, you will research, prototype, evaluate, and productionize techniques that improve model quality and the efficiency of AI workloads on a diverse range of Windows devices. You will work at the intersection of applied machine learning and systems, partnering with software engineers, hardware architects, program managers, and researchers to solve challenges in model optimization, search and retrieval, inference orchestration, and agent execution.
This is an opportunity to turn advances in generative AI, ML/algorithms for search and retrieval, and agentic systems into platform capabilities used by developers and customers at Windows scale.
ResponsibilitiesBringing the State of the Art to Products
- Partners with Engineering and Product teams to turn advances in generative AI, search and retrieval, agentic systems, and efficient inference into measurable product impact. Builds prototypes and production-ready platform components for inference, retrieval, and agent workflows across heterogeneous CPUs, GPUs, and NPUs on Windows devices.
Leveraging Applied Research
- Develops and evaluates data-, research-, and experimentation-backed techniques for on-device and hybrid inference, including quantization, distillation, model adaptation, compression, indexing, embeddings, and hardware-aware optimization. Investigates intelligent model and workload placement across device and cloud resources while balancing quality, latency, memory, power, reliability, privacy, and cost.
Machine Learning Functionality, Insights, and Technical Tools
- Designs datasets, metrics, experiments, and benchmarks for model and system evaluation; analyzes behavior to identify quality and performance bottlenecks and drives improvements across the AI workload lifecycle. Implements and integrates machine learning components, runtimes, developer APIs, and tools, then validates their behavior through production-oriented testing and monitoring on representative hardware and workloads.
Documentation
- Documents scientific approaches, experiment plans, datasets, evaluation results, design decisions, and implementation guidance so that work can be reproduced, reviewed, and adopted by partner teams. Communicates findings through design reviews, technical presentations, and, where appropriate, patents or publications.
Ethics and Privacy
- Applies Responsible AI and Microsoft security principles when selecting data, designing experiments, and developing on-device, hybrid, retrieval, and agent systems. Identifies risks involving privacy, security, bias, and reliability and incorporates appropriate safeguards into technical solutions.
Capability Management and Networking
- Mentors engineers and product partners on applied machine learning, evaluation, inference optimization, search and retrieval, and agent workflows. Builds collaborative relationships across science, engineering, hardware, and product teams; contributes to technical planning and helps teams apply research methods and best practices to platform problems.
QualificationsRequired/Minimum Qualifications:- Bachelor'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 Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research).
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research).
- OR equivalent experience.
Other Requirements: Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
Preferred Qualifications:- Master's Degree in Statistics, Mathematics, Physics, Computer Science, Electrical or Computer Engineering, or a related field AND 6+ years of related experience.
- OR Doctorate in one of these fields AND 2+ years of related experience.
- OR equivalent experience.
- 2+ years of experience developing and deploying production machine learning systems.
- Experience with generative AI, language or multimodal models, agentic systems, model post-training, RAG/Search, Approximate Nearest Neighbor algorithms and ML frameworks.
#W+DJOBS
Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
