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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.
Job Responsibility:
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
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 have:
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