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Microsoft Corporation Logo Microsoft Corporation · IT - Software Development

Senior Research Engineer

United States, Redmond 119800.00 - 234700.00 USD / Year · Job Posted March 21, 2026
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Job Description

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.

Job Responsibility

  • 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
  • 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
  • Specialty Technical Areas
  • Large-scale training and fine-tuning of LLMs, vision-language, or multimodal models
  • Multi-agent systems, dialogue agents, and copilots
  • Optimization of inference speed, accuracy, reliability, and cost in production
  • Retrieval systems and hybrid architectures using RAG and vector databases
  • ML for real-world data constraints such as missing data, noisy labels, and class imbalance

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
  • 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
  • Ability to meet Microsoft, customer and/or government security screening requirements
  • 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 have

  • 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
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Until further notice
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As a Senior Research Engineer at Dynamics 365 Contact Center, you will advance M...
Location
Location
United States , Redmond
Salary
Salary:
119800.00 - 234700.00 USD / Year
https://www.microsoft.com/ Logo
Microsoft Corporation
Expiration Date
Until further notice
Flip Icon
Requirements
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
  • 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 environment
  • 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
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  • 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
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  • identify high-potential methods and adapt them to Microsoft problem spaces
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  • Identify and resolve model quality gaps, latency issues, and scale bottlenecks using PyTorch, or TensorFlow
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