Overview Copilot Discover helps hundreds of millions of people be informed, entertained, and inspired by surfacing highly relevant, trustworthy, and delightful content across Microsoft surfaces. Were building the next generation of AI powered quality understanding and recommendation systems-spanning text, images, audio, and video-to curate the right content at the right moment while upholding safety and integrity. As a Senior Applied Scientist , youll lead the science behind Discovers ranking and contentquality stack, combining LLMs, multimodal models, and largescale recommender systems to drive measurable gains in engagement, satisfaction, and trust. You will set technical direction, mentor a highcaliber science cohort, and partner closely with engineering, PM, UXR, and policy to ship endtoend outcomes. You will contribute to the development of the next generation of MSN that is adopting the latest generative AI techniques. Microsofts 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. Responsibilities Lead contentquality understanding at scale. Design and deploy models that assess credibility, usefulness, freshness, safety, and diversity across modalities; reduce misinformation/toxicity error rates through prompt and modellevel innovations; build humanintheloop and activelearning pipelines that get better over time. Advance the recommendation & ranking stack. Architect and productionize largescale DNN/LLMenhanced recommenders (representation learning, sequence modeling, retrieval/ranking, slate optimization), balancing user satisfaction, content quality, and business goals. Own evaluation and experimentation. Define offline metrics (e.g., NDCG, ERR, calibration) and online methodologies (A/B tests, interleaving, counterfactual & bandit approaches) to confidently attribute impact and guard against regressions. Champion safety & trust. Partner with policy and platform teams to encode safety standards and editorial principles into the ML system; create redteaming, adversarial, and safeguard layers for generative and curated experiences. Scale E2E ML 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 Discovers AI platform. Mentor & influence. Provide technical leadership across problem framing, methodology selection, code quality, and publishing/knowledgesharing; uplevel peers through design reviews, deepdives, and principled decision 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/minimum qualifications Bachelors Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Masters Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. 2+ years of experience working with LLM, NLU or contentquality/safety models at consumer scale, with clear business impact. Preferred Qualifications: Have publications at top AI/ML conferences (e.g., KDD, SIGIR, EMNLP, NIPS, ICML, ICLR, RecSys, ACL, CIKM, CVPR, ICCV, etc.). Expertise with LLMs (prompting, RAG, Parameter-Efficient Fine-Tuning), multimodal modeling, and retrievalaugmented recommendation; familiarity with counterfactual learning and multiobjective optimization. Experience building content integrity/safety systems (e.g., misinformation, harmful content, lowquality/duplicate detection) and qualityaware ranking. Familiarity with Microsoft stack (e.g., Azure ML, Kusto, Synapse, Azure AI Foundry). 2+ years of experience in Python and at least one major deep learning framework (PyTorch/TensorFlow) with largescale data processing and training/inference on distributed systems. 2+ years of evaluation & experimentation (offline metrics, A/B testing, bandits) and ML model development lifecycle. microsoft #hiring #llm #recsys #MicrosoftAI Applied Sciences IC4 - The typical base pay range for this role across Canada is CAD $114,400 - CAD $203,900 per year. Find additional pay information here: Applied Sciences IC4 - Lchelle salariale de base typique pour ce rle dans lensemble du Canada est de 114,400 $ CAD 203,900 $ CAD par anne. Pour plus dinformation au sujet de la rmunration, veuillez cliquer ici: Ce poste sera ouvert pendant au moins cinq jours et les candidatures seront acceptes de faon continue jusqu ce que le poste soit pourvu. This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft est un employeur offrant lgalit daccs lemploi. Tous les candidats qualifis seront pris en considration pour lemploi, sans gard lge, lascendance, la citoyennet, la couleur, aux congs mdicaux ou familiaux, lidentit ou lexpression de genre, aux renseignements gntiques, ltat dimmigration, ltat matrimonial, ltat de sant, lorigine nationale, un ventuel handicap physique ou mental, laffiliation politique, au statut de vtran protg ou au statut militaire, la race, lethnie, la religion, au sexe (y compris la grossesse), lorientation sexuelle ou toute autre caractristique protge par les lois, ordonnances et rglements locaux applicables. Si vous avez besoin daide avec des accommodements religieux et/ou dun accommodement raisonnable en raison dun handicap pendant le processus de candidature, apprenez-en plus sur la demande daccommodement. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
Job Title
Senior Applied Scientist