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As a Principal Research Engineer at Microsoft, you will set the technical vision and lead transformative AI initiatives that shape the future of Microsoft’s products and services. Operating at the intersection of advanced research, engineering, and product strategy, you will drive innovation at scale, architecting solutions that deliver real-world impact for millions of users. You will be a recognised technical leader, influencing cross-organisational strategy, mentoring senior engineers, and representing Microsoft in the global research community.
Job Responsibility:
Define and execute technical strategy for foundational models, multi-agent systems, and next-generation Copilot experiences, especially within Business & Industry Copilot
Lead cross-team efforts to deliver scalable, reliable, and responsible AI systems
Advance the state of the art and translate breakthroughs into measurable customer and business impact
Architect and deliver complex AI systems across model development, data, infra, evaluation, and deployment spanning multiple product lines
Set technical direction for large programs
drive alignment across Research, Engineering, and Product
Integrate LLMs, multimodal models, multi-agent architectures, and RAG into Microsoft’s ecosystem
Establish best practices for MLOps, governance, and Responsible AI, compliant with Microsoft principles and industry standards
Drive original research and thought leadership (whitepapers, internal notes, patents)
convert insights into shipped capabilities
Research Translation: Continuously review emerging work
identify high-potential methods and adapt them to Microsoft problem spaces
Production Integration: Turn research prototypes into production-quality code optimized for scale, latency, and maintainability
ML Design & Architecture: Own end-to-end pipeline from data prep, training, evaluation, deployment, and feedback loops
Evaluation & Instrumentation: Build robust offline/online evals, experimentation frameworks, and telemetry for model/system performance
Learning Loop Creation: Operationalize continuous learning from user feedback and system signals
close the loop from experimentation to deployment
Experimentation & E2E Validation: Design controlled experiments, analyze results, and drive product/model decisions with data
Model Optimization: Select and pursue the right leaderboards and benchmarks for our problem domain
tune/extend models to win where it matters and ensure wins translate to better UX and production metrics
Broker collaborations across Microsoft Research, product engineering, and external partners
Mentor and develop senior engineers and researchers
foster a culture of technical excellence and innovation
Communicate technical vision and results to executives, internal forums, and external audiences
Champion fairness, privacy, and safety end-to-end, design, data, training, evaluation, deployment, and monitoring
Create and drive adoption of internal policies, auditing frameworks, and tools for ethical AI at scale
Requirements:
Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience
Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience
PhD in AI/ML or related field with top-venue publications and/or patents
Experience architecting and deploying LLMs/multimodal models and multi-agent systems in production at scale
Familiarity with Responsible AI frameworks and bias-mitigation techniques
Demonstrated ability to shape product strategy and drive organizational change
Experience with Microsoft’s LLMOps stack: Azure AI Foundry, Azure Machine L
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role
This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter