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Principal Applied Scientist- Foundation Models, Agents & Decision Intelligence

Microsoft· Applied Sciences
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Bangalorefull-timePosted 2mo ago

About the role

Principal Applied Scientist role focused on foundation models, anomaly detection, threat modeling, decision uncertainty, and tool-using agents to support automated and human decisions in Microsoft Advertising. Hands-on end-to-end role from problem formulation to production impact, working with large-scale behavioral and multimodal data to generalize across products and adversarial environments.

Responsibilities

  • 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.

Qualifications

  • 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 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.

Skills

Required:Foundation models / representation learningUncertainty modeling in production systemsPython programmingML frameworks (PyTorch, JAX, TensorFlow)Threat modeling / security awareness
Nice to have:Agentic systems / tool-using agents
Last updated Jul 30, 2026. Interested? Apply on the company site.

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