Principal Applied Scientist at Microsoft | AdTechTalent
Data Science3 months agoOn-site
Microsoft
Principal Applied Scientist
machine learningdeep learningtransformersLLMmultimodalCTRranking modelsadvertisingmodel deploymentdistributed trainingonline servingexperiment designmentorshipresearchproduction systems
Key details
Salary
Not specified
Employment type
Full-time
Seniority
Senior
Years experience
10+
Location
Mountain View, United States; Redmond, United States
Full job description
Seeking a Principal Applied Scientist to lead development of large-scale click-through-rate (CTR) and user response models for Microsoft Advertising. Role involves designing and deploying advanced ML architectures including deep models, transformers, LLM-assisted, and multimodal models. Responsibilities include modernizing modeling pipelines, improving distributed training and online serving, collaborating with product and monetization teams, owning model performance, mentoring scientists and engineers, and driving innovation with LLM-based tooling. Requires advanced degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering or related field with 6+ years experience (Bachelor's +6 years, Master's +4 years, Doctorate +3 years) or equivalent. Preferred candidates have 9+ years experience with Master's or 6+ years with Doctorate, publications, conference presentations, and production system deployment experience. Location is on-site in Redmond, WA or Mountain View, CA. Salary range USD 142,800 - 274,800 per year, higher in SF Bay Area and NYC.
What you'll do
Lead end-to-end development of large-scale CTR and other user response signal models for Search and Display ads
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Mountain View, United States; Redmond, United States
Full-time
Design, prototype, and ship cutting-edge ML architectures including deep models, multi-task, transformer-based, LLM-assisted, multimodal
Define long-term modeling strategy and roadmap with clear business impact
Modernize modeling pipelines addressing technical debt in data flows, training pipelines, and inference systems
Partner with engineering teams to improve reliability, monitoring, and performance of distributed training and online serving
Introduce best practices for experiment design, ablations, feature validation, and productionization
Work with PMs, monetization teams, and auction experts to translate business needs into modeling goals
Own model performance holistically: quality, stability, latency, and revenue impact
Develop frameworks to understand advertiser value, user behavior, and marketplace dynamics
Mentor and up-level applied scientists and ML engineers
Drive a culture of curiosity, deep system understanding, and high-quality scientific reasoning
Improve collaboration norms, documentation quality, and cross-team alignment
Leverage and influence LLM-based tooling to improve team productivity and model development velocity
Identify opportunities to incorporate new modeling signals, architectures, or evaluation metrics
Requirements
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience OR Master's Degree AND 4+ years related experience OR Doctorate AND 3+ years related experience OR equivalent experience
Preferred: Master's Degree AND 9+ years related experience OR Doctorate AND 6+ years related experience OR equivalent experience
5+ years experience creating publications (patents, libraries, peer-reviewed papers)
2+ years experience presenting at conferences or events as invited speaker
5+ years experience conducting research in academic or industry settings
3+ years experience developing and deploying live production systems
3+ years experience developing and deploying products or systems through multiple product cycle stages
Certain roles may be eligible for benefits and other compensationAdditional benefits and pay information available at https://careers.microsoft.com/us/en/us-corporate-pay
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