Senior UX Data Engineer

MicrosoftRedmond, WA
16h

About The Position

Are you an engineer who loves pairing strong product instincts with AI, machine learning, and bringing meaningful UX interactions to life with craft and precision? This role works in a people-centric, culture-first environment alongside designers, product partners, engineers, strategists, and writers to design and build modern experiences that make intelligent systems feel clear, trustworthy, and human. We’re a forward-looking team passionate about building innovative technology and shipping delightful experiences—especially where AI changes what products can do. We invest in rapid prototyping, model tuning and evaluation, data experiments, and AI-related explorations to help explore the future of intelligent Microsoft products. Our team brings diverse backgrounds in multiple disciplines, from engineering, design, or research to behavioral sciences or medicine; we come in all shapes and sizes. We love pushing boundaries and helping evolve Microsoft’s products. Our current focus is on Copilot in the M365 Enterprise world. We're looking for a Senior UX Data Engineer who is self-driven, focused on machine learning, and cares about bringing thoughtful product design to life. You can turn ideas into interactive experiences, learn new tools quickly, and are comfortable exploring the unknown. You value strong engineering practices and know how to collaborate across design and product. You contribute openly, prototype or experiment to learn, share feedback generously, and help raise the quality of the team’s work. You are curious, adaptable, and motivated to build experiences that make a real impact. If you’re looking for a change and wanting to make an impact – we invite you to join us in our mission and vision to build the future of UX for Microsoft.

Requirements

  • Master's Degree in Computer Science, Software Engineering, Graphic Design, Product Design, Visual Design, Human Computer Interaction, or related field AND 3+ years experience working in product or service design and/or shipping production code
  • OR Bachelor's Degree in Computer Science, Software Engineering, Graphic Design, Product Design, Visual Design, Human Computer Interaction, or related field AND 4+ years experience working in product or service design and/or shipping production code
  • OR equivalent experience.
  • GitHub, CodePen, or other links showcasing coding skills OR portfolio is required with application submission.

Nice To Haves

  • Python coding skills and experience with ML frameworks such as PyTorch or TensorFlow
  • Experience working with LLMs, including prompt design, tool and function calling, retrieval strategies (RAG), and multi-step agent orchestration
  • Experience building machine learning pipelines for model quality, optimizations, evaluations, integrations, or UX outcomes (e.g., rubric-based human evals, offline test sets, experiment design, and/or A/B testing), and using results to iterate on both UX and implementation
  • Ability to build and iterate on ML pipelines, integrating insights back into product and experience design
  • Proficiency in data analysis and experimentation to inform product decisions
  • Foundations in linear algebra, calculus, and probability and statistics
  • Familiarity with MLOps and experiment tracking tools like MLflow, Kubeflow, Weights and Biases or equivalent
  • Understanding of production ML requirements, with a track record of mitigating risk and downstream impact
  • Experience with cloud AI and ML services
  • Interest in human-computer interaction, behavioral psychology, and trust in intelligent systems
  • Mastery of at least one back-end coding language
  • Experience building ML-powered product experiences

Responsibilities

  • Design and run applied science and/or machine learning experiments to explore new ideas and validate hypotheses
  • Conduct research on state-of-the-art technologies, methodologies, and emerging trends
  • Translate concepts into working prototypes through code
  • Provide thoughtful, constructive feedback and propose creative, practical solutions
  • Communicate insights, decisions, and results clearly and concisely to cross-functional partners
  • Contribute to publications, technical reports, and knowledge-sharing initiatives
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