Senior Applied AI Scientist

Overview

Microsoft Sentinel Platform NEXT R&D labs is the strategic incubation engine behind the next generation of AI-native security products. We are looking to hire a Senior Applied AI Scientist who thrives in a bottoms-up, fast-paced, highly technical environment. The Sentinel Platform team will be building cloud solutions meeting scales that few companies in the industry are required to support, that leverage state-of-the-art technologies to deliver holistic protection to a planet scale user base. Our team blends scientific rigor, curiosity, and customer obsession to deliver life-changing innovations that protect millions of users and organizations by building the next generation of Artificial Intelligence (AI)-native security products. We pursue long horizon bets while landing near term impact, taking ideas from zero-to-one (0→1) prototypes to Minimum Viable Products (MVPs) and then one-to-many (1→N) platform integration across Microsoft Defender, Sentinel, Entra, Intune, and Purview. Our culture blends ambition and scientific rigor with curiosity, humility, and customer obsession; we invest in new knowledge, collaborate across world-class scientists and engineers, and tackle the immense challenge of protecting millions of customers.

As an Senior Applied AI Scientist, you will lead product-focused applied research and development (R&D) in artificial intelligence and machine learning, driving innovation from concept to production. You will work on a wide range of AI/ML challenges, including, but not limited to, model design, continuous training, optimization, evaluation, and deployment, collaborating with world-class scientists and engineers to deliver robust, scalable, and responsible AI systems for security applications.

Responsibilities

• AI/ML Research: design, development, and analysis of novel AI and machine learning models and algorithms for security and enterprise-scale applications.
• Innovate Across Domains: Explore and apply a broad spectrum of AI/ML techniques, including deep learning, Bayesian probabilistic modeling, classical ML, generative models, and hybrid approaches.
• Experimentation & Evaluation: Design and execute experiments, simulations, and evaluations to validate models and system performance, ensuring measurable improvements.
• Collaboration: Partner with engineering, product, and research teams to translate scientific advances into robust, scalable, and production-ready solutions.
• Customer Impact: Engage with enterprise customers and field teams to co-design solutions, gather feedback, and iterate quickly based on real-world telemetry and outcomes.

Qualifications

Required/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

• Candidates must be able 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.

Additional Or Preferred Qualifications

• 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 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.
• 3+ years working with Machine Learning (ML)/Artificial Intelligence (AI) systems (e.g., Large Language Models (LLM/LRM)/Generative AI (GenAI), retrieval/Retrieval-Augmented Generation (RAG), model serving, experimentation platforms, data pipelines) including establishing evaluation metrics and improving model quality.
• Demonstrated success driving zero-to-one (0→1) initiatives
• ML background and hands-on experience
• Experience with ML lifecycle: model training, fine-tuning, evaluation, continuous monitoring, and more.
• Coding ability in one or more languages (e.g., Python, C#, C++, Rust, JavaScript/TypeScript).
• Familiarity and previous work in the field of cybersecurity (e.g., threat detection/response, SIEM/SOAR, identity, endpoint, cloud security) and familiarity with analyst workflows.

Key skills/competency

• Artificial Intelligence
• Machine Learning
• Deep Learning
• Bayesian Modeling
• Generative AI
• Cybersecurity
• Data Pipelines
• Model Deployment
• Python
• Cloud Security