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We are reimagining Windows in the era of AI. As a Applied Scientist you would play the role of a fullstack AI Builder , and be at the forefront of this transformation—designing, building, and scaling intelligent experiences that blend multimodal input, agentic workflows, and generative AI to make Windows most Inclusive O.S for everyone and people with disabilities. You’ll work in a fast-paced frontier team focused on delivering high-impact features that make Windows more intuitive, inclusive, and human. This role sits within the Windows Empower team, whose mission is to build inclusive, accessible, and empowering experiences for all users—especially those with disabilities. From voice-first interfaces to screen readers and AI-generated speech, we are redefining how people interact with their devices with the power of Human cantered AI. You be deeply involved in Software Development, Testing, Integration, Deployment, Partner collaboration and Innovation aligned with product strategy . You be hands on in building robust, high quality products using cutting edge technology using AI. Hands on development for critical platform features in partnership with other ICs .
Job Responsibility:
Design and implement and experiment end-to-end AI-powered user experiences
Build scalable fullstack solutions that integrate AI models (LLMs, vision, speech) via SDKs, APIs, and custom pipelines
Collaborate with other engineers to optimize model selection, inference performance, and user interaction loops
Partner with PMs, designers, and researchers to prototype and validate new interaction paradigms
Contribute to the architecture and infrastructure for AI-first features, ensuring reliability, privacy, and compliance
Drive engineering excellence through code reviews, testing, telemetry, and continuous improvement
Mentor junior engineers and contribute to a culture of innovation and inclusion
Be a Subject Matter Expert in a specific domain or tech
Be customer and telemetry focussed and reduce mean time to market and mean time to recover through Engineering Excellence
Research and implement state-of-the-art using foundation models, prompt engineering, RAG, graphs, multi-agent architectures, as well as classical machine learning techniques
Fine-tune foundation models using domain-specific datasets
Evaluate model behavior on relevance, bias, hallucination, and response quality via offline evaluations, shadow experiments, online experiments, and ROI analysis
Build rapid Al solution prototypes, contribute to production deployment of these solutions, debug production code, support MLOps/AIOps
Contribute to papers, patents, and conference presentations
Translate research into production-ready solutions and measure their impact through A/B testing and telemetry that address customer needs
Ability to use data to identify gaps in Al quality, uncover insights and implement PoCs to show proof of concepts
Proven programming expertise (e.g., in Python or leveraging Al-first IDEs and SWE agents), with a strong record of building reliable, well-documented research code that drives rapid experimentation, scalable evaluation, and efficient deployment from prototype to production in applied Al research
Demonstrate deep expertise in Al subfields (e.g., deep learning, Generative Al, NLP, muti- modal models) to translate cutting-edge research into practical, real-world solutions that drive product innovation and business impact
Share insights on industry trends and applied technologies with engineering and product teams
Formulate strategic plans that integrate state-of-the-art research to meet business goals
Requirements:
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 or Python
OR equivalent experience
4+ Overall experience End- end shipping of commercial software, with at least 3+ years of experience in AI/ML, predictive analytics or research, and exposure to generative AI/LLM/SLM algorithms
A Customer focused innovation mindset
Passionate about Craftmanship in engineering
Experience building AI/ML solutions is good to have
Aptitude to learn and adapt with intensity and agility
Nice to have:
8+ Overall experience End- end shipping of commercial software
Experience with cross group design and coordination is an advantage