# Principal Applied Scientist

**Company**: Microsoft
**Location**: Mountain View
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: $163,000 – $296,400 per year
**Category**: Engineering
**Industry**: Technology
**Ticker**: MSFT
**Wikidata**: https://www.wikidata.org/wiki/Q2283

**Apply**: https://microsoft.ai/job/principal-applied-scientist-24/
**Canonical**: https://yubhub.co/jobs/job_86d393d4-2af

## Description

We're building the next generation of AI-powered content recommendation systems,spanning text, images, audio, and video,to curate the right content at the right moment for each user while upholding safety and integrity.

As a Principal Applied Scientist, you’ll lead the science behind Discover’s ranking, user understanding, and content understanding stack, combining LLMs, multimodal models, and large-scale recommender systems to drive measurable gains in engagement, satisfaction, and trust.

You will set technical direction, mentor a high-caliber science cohort, and partner closely with engineering, PM, UXR, and policy to ship end-to-end outcomes.

Responsibilities: Advance the recommendation & ranking stack. Architect and productionize large-scale DNN/LLM-enhanced recommenders (representation learning, sequence modeling, retrieval/ranking, slate optimization), balancing user satisfaction, content quality, and business goals. Deepen user & content understanding. Gather and analyze user signals from diverse sources to gain a thorough understanding of user behaviors and utilize ML/AI techniques to interpret and predict user needs and preferences. Design and build models that assess content quality and utility aspects to ensure product safety and drive sustainable user engagement. Scale E2E ML/AI systems. Collaborate with engineering on data contracts, feature stores, distributed training/inference, and automated rollout/rollback; drive architectural investments that increase agility and reliability of Discover’s AI platform. Drive innovation in AI-forward products. Collaborate with product, science and engineering team closely to innovate in AI-forward products, including agentic content feed experience with hyper personalized AI-generated content and generative UI. Mentor & influence. Provide technical leadership across problem framing, methodology selection, code quality, and publishing/knowledge-sharing; uplevel peers through design reviews, deep-dives, and principled decision-making. Stay close to users. Translate user engagements and behavioral history into model objectives and product bets; ensure our AI solutions elevate relevance, transparency, and engagement for real users.

Qualifications: Required Qualifications: Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. Preferred Qualifications: Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 12+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. 6+ years of industry experience on applied AI/ML for web scale products. Having publications at top AI/ML conferences (e.g., KDD, SIGIR, NIPS, ICML, ICLR, RecSys, ACL, CIKM, CVPR, ICCV, etc.). Demonstrated capability to grow the business through the innovation of ML algorithms. Experience in Software Engineering and familiar with ML Infra.

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