Data Scientist focused on large-scale recommendation systems and agentic AI at Glance.
Responsibilities
Design and develop large-scale recommendation systems using advanced ML, statistical modeling, ranking algorithms, and deep learning.
Build and operate machine learning models on diverse, high-volume data sources for personalization, prediction, and content understanding.
Develop rapid experimentation workflows to validate hypotheses and measure real-world business impact.
Own data preparation, model training, evaluation, and deployment pipelines in collaboration with engineering counterparts.
Monitor ML model performance using statistical techniques; identify drifts, failure modes, and improvement opportunities.
Requirements
Bachelor’s/Master’s in Computer Science, Statistics, Mathematics, Electrical Engineering, Operations Research, Economics, Analytics, or related fields. PhD is a plus.
Build production machine learning solutions that improve employee experiences and inform workforce decisions using economics, behavioral science, statistics, and machine learning.
Develop highly scalable algorithms based on state-of-the-art machine learning and neural network methodologies and research, design, and develop new algorithms and techniques to improve the efficiency and performance of Meta's platforms.
Locations (4)
Redmond, Washington, United States
Burlingame, California, United States
New York, New York, United States
Seattle, Washington, United States
Responsibilities
Develop highly scalable algorithms based on state-of-the-art machine learning and neural network methodologies
Suggest, collect, and synthesize requirements and create effective feature roadmap
Develop the next generation Image Search Quality stack, designing and implementing AI-centric workflows to fulfill quality objectives within Google Search AI.
Lead Search and Discovery product strategy for YouTube Live, driving real-time recommendation systems and integrating live discovery mechanics into core YouTube surfaces.
Locations (2)
San Bruno, California, United States
Mountain View, California, United States
Compensation
US: $240000 - $333000 (USD) + 25% bonus target
Responsibilities
Lead Search and Discovery product strategy, responsible for outlining goals and delivering significant and predictable annual topline impact for all YouTube Live.
Act as the primary bridge to core YouTube Search and Discovery teams by advocating for, negotiating, and integrating Live discovery mechanics into core surfaces like the YouTube Home Feed, Search infrastructure, and Watch Next models.
Build technically sophisticated perspectives on recommendation systems, ranking models, and information retrieval infrastructures, partnering with engineering to push the boundaries of real-time personalization.
USA, CA, San Francisco - 171,600.00 - 222,200.00 USD annually
USA, MA, Boston - 142,800.00 - 193,200.00 USD annually
USA, VA, Arlington - 142,800.00 - 193,200.00 USD annually
USA, WA, Bellevue - 142,800.00 - 193,200.00 USD annually
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually
Responsibilities
Design, develop, and deploy machine learning solutions in production environments
Develop solutions using techniques that include predictive modeling, deep learning, natural language processing, recommendation systems, personalization, and generative AI
Build models that predict workforce outcomes, identify employee and organizational needs, and recommend targeted actions
Partner with economists and other scientists to design causal evaluations and experimental frameworks that measure the impact of programs, products, and policies
Combine predictive models with causal estimates to help business partners identify effective actions and make evidence-based decisions
Requirements
PhD
Master's degree
Nice to have: professional software development
Nice to have: building machine learning models for business application
health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
Secure executive buy-in across fragmented product organizations, aligning stakeholders behind a cohesive, high-velocity roadmap.
Keep a continuous pulse on the shifting live streaming and creator economy landscapes to rapidly turn participant advantages or inefficiencies into YouTube feature innovations.
Requirements
Bachelor's degree or equivalent practical experience
Nice to have: Master's degree in a technology or business related field
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