Senior Research Engineer

Microsoft•Redmond, WA

About The Position

As a Senior Research Engineer at Microsoft, you will advance Microsoft’s mission to empower every person and every organization to achieve more. You will help build and integrate cutting-edge AI into Microsoft products and services within the Business & Industry Copilot (BIC) group, ensuring solutions are inclusive, ethical, and impactful. This role blends applied research, machine learning engineering, and product innovation. You will lead efforts to ship reliable, production-grade AI systems across the stack, from model development and fine-tuning to performance optimization and deployment. Mission and Impact We are in an era of unprecedented AI innovation. As Microsoft leads the way in foundation models, multimodal systems, and AI agents, our goal is to build an open architecture platform where users can interact with tailored AI agents that drive tangible, real-world outcomes. As a Senior Research Engineer, you will: Bridge the gap between state-of-the-art research and customer-facing features Drive systems-level innovation across models, infrastructure, and deployment Champion responsible AI by embedding fairness, safety, privacy, and performance from the ground up Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Requirements

Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
Experience deploying Fine Tuned LLMs or multimodal models in live production environments.
Experience shipping and maintaining production AI systems.
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 Cloud background check upon hire/transfer and every two years thereafter.

Nice To Haves

Master'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 Bachelor'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 equivalent experience.
Experience with Microsoft’s LLMOps stack: Azure AI Foundry, Azure Machine Learning, Semantic Kernel, Azure OpenAI Service, and Azure AI Search for vector/RAG.
Familiarity with responsible AI evaluation frameworks and bias mitigation methods.
Experience across the product lifecycle from ideation to shipping.

Responsibilities

Bringing State-of-the-Art Research to Products Design and implement AI systems using foundation models, prompt engineering, retrieval-augmented generation, multi-agent architectures, and classic ML
Fine-tune large language models on domain-specific data and evaluate via offline and online methods such as A/B testing, telemetry, and shadow deployments
Build and harden prototypes into production-ready services using robust software engineering and MLOps practices
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 End-to-End System Development ML Design & Architecture: Own end-to-end pipeline from data prep, training, evaluation, deployment, and feedback loops
Identify and resolve model quality gaps, latency issues, and scale bottlenecks using PyTorch, or TensorFlow
Operate CI/CD and MLOps workflows including model versioning, retraining, evaluation, and monitoring
Integrate AI components into Microsoft products in close partnership with engineering and product teams Data-Driven Innovation 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.
Develop proofs of concept that validate ideas quickly at realistic scales
Curate high-signal datasets, including synthetic and red-team corpora, and establish labeling protocols and data quality checks tied to evaluation KPIs Cross-Functional Collaboration Partner with software engineers, scientists, designers, and product managers to deliver high-impact AI features
Translate research breakthroughs into scalable applications aligned with product priorities
Communicate findings and decisions through internal forums, demos, and documentation Responsible AI & Ethics Identify and mitigate risks related to fairness, privacy, safety, security, hallucination, and data leakage
Uphold Microsoft’s Responsible AI principles throughout the lifecycle
Contribute to internal policies, auditing practices, and tools for responsible AI Operating Altitudes Paper level (ideas and math): Read, critique, and adapt the latest research; identify gaps; design methods with clear trade-offs and guarantees; communicate complex ideas clearly.
Code level (implementation): Turn ideas into robust, tested, maintainable modules; integrate with CI/CD; profile and optimize for latency and throughput.