{"id":3848777,"url":"https://alion.io/job/microsoft-senior-machine-learning-engineer-applied-scientist-3","title":"Senior Machine Learning Engineer / Applied Scientist","company":{"id":18,"name":"Microsoft","domain":"microsoft.com","url":"https://alion.io/company/microsoft","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"B","score":84,"open_postings":456,"ghost_share":0.007,"stale_share":0.59,"repost_share":0.039,"time_to_fill_p50_days":29,"computed_at":"2026-11-07T05:47:08Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Vancouver, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":114400,"max":203900,"currency":"CAD","period":"year","gross":null,"usd_annual":145703},"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"RAG","optional":false},{"name":"Agentic Workflows","optional":true},{"name":"AI Agents","optional":true},{"name":"Function Calling","optional":true},{"name":"LLM","optional":true}],"status":"live","first_seen_at":"2026-11-03T12:59:09Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-07T21:27:53Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"OverviewWe are looking for a Senior Machine Learning Engineer / Applied Scientist to help design, evaluate, and ship the next generation of AI-powered product experiences. The role combines strong machine learning and applied science depth with hands-on engineering, product judgment, and end-to-end ownership from prototyping through launch and continuous improvement.\nMicrosoft’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.\nResponsibilities\nBuild, evaluate, and improve AI/ML experiences (LLMs, RAG, agentic, multimodal systems).\n\nDesign evaluation frameworks for quality, grounding, reliability, safety, and UX.\n\nBuild offline experimentation pipelines for models/prompts/retrieval/system designs.\n\nPartner across product/engineering/science to define measurable objectives and success metrics.\n\nAnalyze failures and drive clear product/technical improvements.\n\nBuild production-grade ML systems (scalability, latency, reliability, observability, maintainability).\n\nContribute to MLOps (data pipelines, telemetry, regression testing, monitoring).\n\nCommunicate risks/tradeoffs/recommendations and mentor peers.\n\nQualifications\nRequired Qualifications:\nBachelor's 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 Master's 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.\nOther Requirements:\nAbility to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:\nMicrosoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.\nPreferred Qualifications:\nMaster'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 3+ years related experience (e.g., statistics, predictive analytics, research) \nOR equivalent experience.\n\n3+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).\nExperience presenting at conferences or other events in the outside research/industry community as an invited speaker.\n3+ years experience conducting research as part of a research program (in academic or industry settings).\n1+ year(s) experience developing and deploying live production systems, as part of a product team.\n1+ year(s) experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.\nExperience building, evaluating, and shipping production AI/ML systems.\nHands-on LLM experience (prompting, evaluation, RAG, agents/tool use, failure analysis).\nSolid software engineering skills for reliable, maintainable systems.\nExperience designing experiments and using data to drive decisions.\nUnderstanding of evaluation methods, dataset/annotation strategy, benchmarks, regression testing, and production monitoring.\nAbility to translate customer/product goals into measurable technical/scientific objectives.\nSolid cross-functional collaboration and communication skills.\nExperience building and shipping AI/ML systems in production, including LLM-based applications.\nExperience with evaluation frameworks for model quality, reliability, grounding, safety, and user impact.\nSolid background in experimentation, error analysis, and data-driven model/system improvement.\nExperience with retrieval-augmented generation (RAG), agentic workflows, and multimodal AI systems.\nPublications, patents, or other recognized technical contributions in AI/ML.\nApplied Sciences IC4 - The typical base pay range for this role across Canada is CAD $114,400 - CAD $203,900 per year.\nFind additional pay information here:\nhttps://careers.microsoft.com/v2/global/en/canada-pay-information.html\nApplied Sciences IC4 - L'échelle salariale de base typique pour ce rôle dans l'ensemble du Canada est de 114,400 $ CAD à 203,900 $ CAD par année. \nPour plus d'information au sujet de la rémunération, veuillez cliquer ici:\nhttps://careers.microsoft.com/v2/global/en/canada-pay-information.html\nCe poste sera ouvert pendant au moins cinq jours et les candidatures seront acceptées de façon continue jusqu’à ce que le poste soit pourvu.\nThis position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.\nMicrosoft est un employeur offrant l’égalité d’accès à l’emploi. Tous les candidats qualifiés seront pris en considération pour l’emploi, sans égard à l’âge, à l’ascendance, à la citoyenneté, à la couleur, aux congés médicaux ou familiaux, à l’identité ou à l’expression de genre, aux renseignements génétiques, à l’état d’immigration, à l’état matrimonial, à l’état de santé, à l’origine nationale, à un éventuel handicap physique ou mental, à l’affiliation politique, au statut de vétéran protégé ou au statut militaire, à la race, à l’ethnie, à la religion, au sexe (y compris la grossesse), à l’orientation sexuelle ou à toute autre caractéristique protégée par les lois, ordonnances et règlements locaux applicables. Si vous avez besoin d’aide avec des accommodements religieux et/ou d’un accommodement raisonnable en raison d’un handicap pendant le processus de candidature, apprenez-en plus sur la demande d’accommodement.\nMicrosoft 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. 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