About the job
Have you ever wondered what it takes to transform millions of manual network planning decisions into AI-powered precision? Network Planning Solutions is looking for scientific innovators obsessed with building the AI/ML intelligence that makes orchestrating complex global operations feel effortless. Here, you'll do more than just build models; you'll create 'delight' by discovering and deploying the science that delivers exactly what our customers need, right when they need it. If you're ready to transform complex data patterns into breakthrough AI capabilities that power intuitive human experiences, you've found your team.
Responsibilities
Develop and deploy production-ready demand forecasting algorithms that continuously sense and predict customer demand using real-time signals
Build network optimization algorithms that automatically adjust staffing as conditions evolve across the service network
Architect scalable AI/ML infrastructure supporting automated forecasting and network optimization capabilities across the system
Build and mentor a team of applied scientists to deliver breakthrough AI/ML solutions
Design rigorous experiments to validate hypotheses and quantify business impact
Establish scientific excellence mechanisms including evaluation metrics and peer review processes
Drive scientific innovation from research to production - Design and validate next-generation AI-native models while ensuring robust performance, explainability, and seamless integration with existing systems.
Partner with Engineering, Product, and Operations teams to translate AI/ML capabilities into measurable business outcomes
Navigate ambiguity through experimentation while balancing innovation with operational constraints
Influence senior leadership through scientific rigor, translating complex algorithms into clear business value
Qualifications
Minimum
10+ years of building large-scale machine learning and AI solutions at Internet scale experience
Master's degree in Computer Science (Machine Learning, AI, Statistics, or equivalent)
Experience building large-scale machine learning and AI solutions at Internet scale
Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track
Preferred
10+ years of practical work applying ML to solve complex problems for large-scale applications experience
5+ years of hands-on work in big data, machine learning and predictive modeling experience
5+ years of people management experience
PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent)
Experience in practical work applying ML to solve complex problems for large scale applications
Experience developing, deploying and managing AI products at scale
Experience building complex highly-scalable systems that involve predictive models or applications of machine learning