Microsoft · 15 hours ago
Principal Applied AI/ML Research Scientist
Redmond, WA
Full-time
Hybrid
Senior Level, Lead/Staff
$140K/yr - $275K/yr
5+ years expMicrosoft is focused on reshaping security and empowering users with a security cloud. The Applied AI/ML Research Scientist will develop and deploy advanced machine learning and AI models for data classification, collaborating with various teams to deliver impactful solutions.
Agentic AIApplication Performance ManagementArtificial Intelligence (AI)Business DevelopmentDevOpsInformation ServicesInformation TechnologyManagement Information SystemsNetwork SecuritySoftware
Responsibilities
Own end-to-end delivery: Lead the full modeling lifecycle for security scenarios, from data ingestion and curation to training, evaluation, deployment, and monitoring. Problem framing, literature review, model design, offline evaluation, online experimentation, and production deployment
Implement and optimize models: Design and implement privacy-preserving data workflows, including anonymization, templating, synthetic augmentation, and quantitative utility measurement. Develop and maintain fine-tuning and adaptation recipes for transformer models, including parameter-efficient methods and reinforcement learning from human or synthetic feedback. Establish objective benchmarks, metrics, and automated gates for accuracy, robustness, safety, and performance, enabling repeatable model shipping
Productionize AI & ML Collaborate with engineering and product teams to productionize models, harden pipelines, and meet service-level objectives for latency, throughput, and availability. Develop fine-tuning techniques for transformer models and establish benchmarks for accuracy, robustness, and performance to ensure reliable model delivery. Drive MLOps best practices: CI/CD, model registry, feature store, model serving, monitoring/drift
Champion Responsible AI: fairness, explainability, privacy (GDPR/CCPA) and security considerations in model design and deployment
Operational excellence: code quality, tests, observability (logs/metrics/traces), on-call ownership for ML services, and SLA adherence
Collaborate cross‑functionally: write design docs/RFCs, partner with PMs and engineers, and drive execution towards predictable outcomes and timelines
Qualification
Required
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience
Ability 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 background and Microsoft Cloud background check upon hire/transfer and every two years thereafter
Preferred
GenAI experience: fine‑tuning, instruction tuning, RAG pipelines, evaluation harnesses (e.g., task-specific metrics, human-in-the-loop)
Strong software engineering: Python + one systems language (C++/Java/Go/Rust), data structures/algorithms, code reviews, testing
MLOps expertise: CI/CD (GitHub Actions/Azure DevOps), containers (Docker), orchestration (Kubernetes), model registry/feature store, monitoring & drift detection
Experimentation: A/B testing design, statistical rigor; metrics for model quality and business impact (precision/recall, ROC/AUC, NDCG/MAP, uplift)
Data engineering: SQL, Spark/Databricks, data modeling, data quality and reproducibility
Communication & execution: clear writing, design docs, stakeholder alignment, and consistent delivery to milestones
Proven track record of shipping ML systems to production at scale (not just prototypes); portfolio or references welcome
Applied research skills: reading SOTA literature, rapid replication, hypothesis-driven iteration, and practical adaptation to product constraints
Company
Microsoft
Microsoft is a software corporation that develops, manufactures, licenses, supports, and sells a range of software products and services.
10001+ employees
H1B Sponsorship
Microsoft has a track record of offering H1B sponsorships. Please note that this does not
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2025 (9192)
2024 (9343)
2023 (7677)
2022 (11403)
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2020 (7852)
Funding
Current Stage
Public CompanyTotal Funding
$1MKey Investors
Technology Venture Investors
2022-12-09Post Ipo Equity
1986-03-13IPO
1981-09-01Series Unknown· $1M
Leadership Team
Satya Nadella
Chairman and CEO
Vukani Mngxati
Chief Executive Officer - Microsft South Africa
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