Principal Applied Scientist- Foundation Models, Agents & Decision Intelligence

About the Role

Microsoft Advertising is building the next generation of AI systems for understanding advertiser behavior detecting anomalies and emerging threats.

We are looking for a Principal Applied Scientist with a strong foundation in mathematics statistics and core machine learning to advance:

• Foundation models for behavioral content entity and risk understanding.
• Anomaly detection and threat modeling for new and evolving abuse patterns.
• Decision uncertainty modeling across models agents workflows and human review.
• Tool-using agents that investigate cases gather evidence and support automated and human decisions.
• Rigorous evaluation of models agents and end-to-end decision systems.

You will work with large-scale behavioral multimodal temporal and relational data to build capabilities that generalize across products markets policies and changing adversarial environments.

This is a hands-on scientific role with end-to-end ownership from problem formulation and model development through large-scale training evaluation productionization and measurable product impact

• Define and lead scientific initiatives in one or more areas eg foundation models behavioral modeling anomaly detection threat modeling agentic systems.
• Develop scalable learning systems that understand entities content relationships and behavior over time while identifying known emerging and previously unseen risks.
• Develop methods to model and propagate uncertainty across individual models model cascades agent trajectories retrieved evidence automated decisions and human judgments.
• Use uncertainty confidence severity and business impact to determine when to automate gather additional evidence invoke a more capable system abstain or escalate to expert review.
• Translate threat models and adversarial insights into data strategies learning objectives model architectures agent capabilities and evaluation plans.
• Advance the training post-training and evaluation of agents that use tools and evidence to investigate complex cases and produce grounded outcomes.
• Address challenging learning settings involving distribution shift sparse or delayed labels noisy supervision class imbalance selective observation and adaptive adversaries.
• Translate scientific advances into reliable efficient and measurable production capabilities across Microsoft Advertising.
• Provide technical leadership mentor scientists and influence the long-term architecture of AI-driven trust and safety systems.

• Bachelors Masters or Doctorate degree in Computer Science Mathematics Statistics Electrical Engineering Operations Research or a related quantitative field with relevant industry or research experience .
• Strong foundation in probability statistics linear algebra optimization numerical methods experimental design and statistical decision theory.
• Deep expertise in modern machine learning including foundation or representation learning behavioral and temporal modeling anomaly detection.
• Proven experience in post-training and evaluating large-scale models (xxx B param)
• Experience modeling uncertainty in production decision systems.
• Ability to model threat and abuse scenarious.
• Strong programming skills in Python and experience with frameworks such as PyTorch JAX TensorFlow or equivalent technologies.
• Proven ability to take scientific ideas from formulation through experimentation production deployment and measurable impact.
• Demonstrated technical leadership through scientific direction architecture mentorship and influence across science engineering product and security teams.

Preferred Qualifications

• Experience with tool-using agents retrieval agent post-training reward modeling or trajectory evaluation.
• Experience in trust and safety fraud abuse cybersecurity moderation account integrity or policy enforcement.
• Experience working with temporal multimodal heterogeneous or graph-structured data.
• Strong publication or production track record in machine learning agents anomaly detection probabilistic modeling adversarial ML multimodal learning or trust and safety.

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.

Required Experience:

IC