Staff Applied Scientist - Recommendation Systems

Responsibilities

• Design, build, and deploy large-scale recommendation and personalization models using diverse, high-volume data sources
• Lead rapid experimentation including hypothesis formulation, offline evaluation, and online A/B testing
• Develop and productionize end-to-end ML pipelines covering data preparation, feature engineering, model training, and monitoring
• Partner with Product, Engineering, Design, UX, and Business teams to translate product goals into scalable ML solutions
• Monitor model health and performance using statistical techniques
• Explore and prototype new ML techniques to improve relevance, engagement, and monetization
• Act as a technical interface for stakeholders to articulate trade-offs and results
• Contribute to thought leadership through blogs, case studies, and industry talks

Requirements

• 10+ years of industry experience in ML/Data Science building large-scale recommendation or personalization systems
• Deep expertise in Machine Learning, Data Science, and Recommendation Systems at scale
• Strong applied understanding of experimentation, metrics, and causal reasoning
• Hands-on experience with ML, Deep Learning, NLP, Reinforcement Learning, Time Series, and Statistics
• Strong Python programming skills with production-quality code practices
• Experience with big data ecosystems, specifically Apache Spark
• Familiarity with cloud platforms such as AWS, GCP (Vertex AI), or Azure
• Bachelor’s or Master’s degree in a quantitative field (Computer Science, Statistics, Mathematics, etc.)

Preferred Qualifications

• PhD in a quantitative field
• Experience operating in identity-constrained or privacy-aware environments (e.g., iOS/Android)

About the Company

Glance AI is an AI commerce platform shaping the next wave of e-commerce through inspiration-led discovery. Part of the InMobi Group, Glance transforms screens into stages for personal shopping experiences across 140 countries.