About the job
As a Senior Research Engineer at Microsoft, you will help advance Microsoft’s mission to empower every person and every organization on the planet to achieve more by building intelligent, scalable cloud services that power Dynamics 365 Contact Center. This role sits at the intersection of AI, software engineering, and enterprise customer engagement. You will contribute to the design and delivery of AI-first capabilities that enable organizations to connect with, understand, and serve their customers across digital and voice channels.
Responsibilities
Build AI-First Contact Center Experiences
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
Partner with product teams to improve customer and agent outcomes
End-to-End System Development
Own features end-to-end from design to live-site operations
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 Engineering
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
Qualifications
Minimum
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 PythonOR equivalent experience.
Proficiency in Python and at least one deep learning framework such as PyTorch, JAX, or TensorFlow.
Experience deploying Fine Tuned LLMs or multimodal models in live production environments.
Experience shipping and maintaining production AI systems.
Preferred
Master’s degree and 3 or more years in applied ML or AI research and product engineering,OR PhD in a relevant field and 2 or more years with generative AI, LLMs, or related ML algorithms. 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.