Principal AI Scientist at Microsoft

, , United States -

Full Time

Start Date

Immediate

Expiry Date

20 Feb, 26

Salary

0.0

Posted On

22 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI/ML Research, Deep Learning, Bayesian Probabilistic Modeling, Classical ML, Generative Models, Hybrid Approaches, Experimentation, Evaluation, Mentorship, Responsible AI, Security Domain Expertise, Model Quality Improvement, Hands-On Coding, Collaboration, Customer Engagement, Clear Communication

Industry

Software Development

Description

Lead AI/ML Research: Drive the 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. Mentorship & Thought Leadership: Mentor other scientists and engineers, foster a culture of scientific rigor and curiosity, and contribute to the broader research community through publications, talks, or open-source contributions. Responsible AI: Ensure privacy, security, and responsible AI guardrails are designed in from day one, coordinating safety reviews, compliance, and incident readiness. 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. Bachelor'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 Master'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 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. These requirements include, but are not limited to the following specialized security screenings: Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ 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. 3+ years experience developing and deploying live production systems, as part of a product team. Hands-on coding ability in one or more languages (e.g., Python, C#, C++, Rust, JavaScript/TypeScript). Security domain expertise (e.g., threat detection/response, SIEM/SOAR, identity, endpoint, cloud security) and familiarity with analyst workflows Ability to Dmeostrate when to use Bayesian models, when to apply classical ML, and how to hybridize them to meet business and technical objectives. Evaluation-obsessed: You define the right metrics, build evaluation harnesses, and insist on measurable improvements before broad rollout. Clear communicator and connector: You create clarity in ambiguity, align diverse stakeholders, and mentor others to raise the bar.

Responsibilities

Lead the design, development, and analysis of novel AI and machine learning models for security applications. Collaborate with engineering and product teams to translate scientific advances into production-ready solutions.