Principal Applied Science Manager - CoreAI at Microsoft

Redmond, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

14 Apr, 26

Salary

296400.0

Posted On

14 Jan, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Artificial Intelligence, Machine Learning, Data Generation, Model Alignment, Evaluation Frameworks, Cross-Functional Collaboration, Technical Leadership, People Management, Deep Learning, Transformer-Based Models, Problem-Solving, Analytics, Safety, Research, Software Engineering, Distributed Systems

Industry

Software Development

Description

Overview The CoreAI organization at Microsoft builds the end-to-end Artificial Intelligence (AI) stack and is core to Azure AI innovation and differentiation, as well as all of Microsoft’s flagship products, from GitHub, to Office, Teams, and Xbox. We are the team building Responsible AI, Azure OpenAI, Model as a Service, Azure Machine Learning (ML), Cognitive Services, and the global Azure AI infrastructure for running the largest AI workloads on the planet. We are hiring a Principal Applied Science Manager to join our team! We ensure Microsoft ships AI systems that are safe, secure, and trustworthy—empowering every person and organization on the planet to achieve more. Our team sits at the intersection of cutting-edge AI research and planet-scale production systems, powering technologies like GitHub Copilot and Azure OpenAI. Responsibilities Lead the development and deployment of novel fine-tuning techniques that leverage synthetic data generation, preference modeling, and advanced training pipelines (e.g., SFT, RL-based methods, hybrid approaches) to improve model alignment at scale. Apply these techniques to train models with stronger alignment properties, including honesty, character, harmlessness, and robustness to misuse, distribution shift, and adversarial inputs. Design, build, and maintain rigorous evaluation frameworks to measure alignment and safety properties across capabilities, failure modes, and deployment contexts, including offline benchmarks, automated probes, and human-in-the-loop evaluations. Collaborate cross-functionally with research, product, infrastructure, and deployment teams to translate alignment improvements into production-ready models, balancing safety, capability, latency, and cost considerations. Establish scalable processes and tooling to automate data generation, training, evaluation, and analysis workflows, enabling the team to iterate rapidly and operate reliably as model size, complexity, and deployment surface grow. Provide technical leadership and people management for a team of applied scientists and engineers, setting clear technical direction, prioritizing high-impact work, and mentoring team members in both research rigor and production excellence. Influence the broader safety and alignment strategy by identifying emerging risks, proposing new mitigation approaches, and contributing to long-term roadmaps for responsible model development. Qualifications Required Qualifications: Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ 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 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. 3+ years of people management 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: Experience and familiarity with large language models (LLMs). Experience with and a solid foundation in large distributed systems, algorithms, and software engineering principles. 5+ years of experience in a research/ML engineering or an applied research scientist position, ideally with a focus on AI safety. Have hands-on experience with deep learning and transformer-based models Excel at problem-solving and analytics, with a proactive approach to challenges Thrive in fast-moving environments where priorities shift and definitions evolve. Enjoy taking ownership end-to-end and learning whatever is necessary to get results. Comfortable working independently while thriving in cross-team collaborations. Understand methods for training and fine-tuning LLMs, including distillation, supervised fine-tuning, and policy optimization. #coreai Applied Sciences M6 - The typical base pay range for this role across the U.S. is USD $163,000 - $296,400 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 $220,800 - $331,200 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. 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.

Responsibilities

Lead the development and deployment of novel fine-tuning techniques for AI models, focusing on improving model alignment at scale. Collaborate with cross-functional teams to translate alignment improvements into production-ready models while ensuring safety and capability.