Senior Applied Scientist Job at Microsoft Corporation (Vancouver)

Senior Applied Scientist

Microsoft Corporation

Location:
Canada , Vancouver

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

114400.00 - 203900.00 CAD / Year

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Job Description:

Copilot Discover helps hundreds of millions of people be informed, entertained, and inspired by surfacing highly relevant, trustworthy, and delightful content across Microsoft surfaces. We’re 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, you’ll lead the science behind Discover’s ranking and content‑quality 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. You will contribute to the development of the next generation of MSN that is adopting the latest generative AI techniques.

Job Responsibility:

Lead content‑quality 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 model‑level innovations
build human‑in‑the‑loop and active‑learning pipelines that get better over time
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
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 red‑teaming, 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 Discover’s AI platform
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‑
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

Requirements:

Bachelor'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
2+ years of experience working with LLM, NLU or content‑quality/safety models at consumer scale, with clear business impact

Nice to have:

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 retrieval‑augmented recommendation
familiarity with counterfactual learning and multi‑objective optimization
Experience building content integrity/safety systems (e.g., misinformation, harmful content, low‑quality/duplicate detection) and quality‑aware 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 large‑scale data processing and training/inference on distributed systems
2+ years of evaluation & experimentation (offline metrics, A/B testing, bandits) and ML model development lifecycle

Additional Information:

Job Posted:
February 17, 2026

Employment Type:

Fulltime

Work Type:

On-site work

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