Microsoft Advertising seeks a Principal Applied Scientist with expertise in mathematics, statistics, and machine learning to lead initiatives in foundation models, behavioral modeling, anomaly detection, threat modeling, and agentic systems. Responsibilities include developing scalable learning systems, modeling uncertainty, translating threat models into data strategies, advancing agent training and evaluation, addressing complex learning challenges, and providing technical leadership. Requirements include advanced degree in quantitative field, strong foundation in probability and statistics, expertise in modern machine learning, experience with large-scale model evaluation, uncertainty modeling, threat modeling, programming skills in Python and ML frameworks (PyTorch, JAX, TensorFlow), and proven scientific leadership.
What you'll do
Define and lead scientific initiatives in one or more areas eg foundation models, behavioral modeling, anomaly detection, threat modeling, agentic systems
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Requirements
Bachelor’s, Master’s, 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 scenarios
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
Tech stack
PythonPyTorchJAXTensorFlow
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