New 
Principal Applied Scientist
 Microsoft | |
 United States, Washington, Redmond | |
 Oct 07, 2025 | |
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OverviewAbout Microsoft Shopping: As Microsoft continues to push the boundaries of AI, our vision is bold and transformative: to reinvent online shopping experiences for hundreds of millions of users worldwide. Microsoft Shopping empowers customers to find what they want quickly and confidently by surfacing the most relevant products at the best prices from across the web. Our team operates at true web scale-connecting billions of products from merchants globally and delivering rich shopping experiences across Bing, Edge, MSN, and Copilot. We combine cutting-edge information retrieval, recommendation systems, and generative AI to help users make informed purchase decisions. As part of the Microsoft AI (MAI) organization, our work directly drives critical Microsoft businesses and shapes the future of commerce. If you have a keen interest in solving complex AI challenges, building systems that operate at massive scale, and leading innovation in personalization and relevance, this is the team for you. We move fast, uphold a high bar for quality, and are committed to using data and AI to create delightful, trusted shopping experiences for everyone. Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50-mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.
ResponsibilitiesLead cutting-edge ML development: Design and refine advanced ranking algorithms using transformer-based architectures, semantic embeddings, and LLM fine-tuning techniques (e.g., knowledge distillation, LoRA, quantization) to deliver world-class relevance under strict latency constraints.Set the standard for evaluation: Define and evolve methodologies for both automated and human evaluations, ensuring comprehensive coverage and actionable insights.Architect scalable data systems: Build and optimize pipelines that transform massive product and interaction logs into structured datasets for model training and evaluation.Drive production excellence: Partner with engineering teams to deploy models at scale, optimize inference for p95 latency targets, and implement robust monitoring for reliability and performance.Shape AI strategy: Stay ahead of the curve on LLM research, prompting techniques, and evaluation frameworks and translate these advancements into real-world impact.Deliver business-critical insights: Lead deep-dive analyses on large-scale telemetry to uncover opportunities, guide product direction, and influence key metrics.Mentor and inspire: Provide technical leadership, coach top talent, and raise the bar for the team's research and engineering practices. | |