Applied Scientist II - Recommendation Systems

Responsibilities

• Design and develop large-scale recommendation systems using advanced ML, statistical modelling, 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 to identify drifts and failure modes
• Collaborate with Designers, UX Researchers, Product Managers, and Software Engineers to integrate ML and GenAI-driven features

Requirements

• Bachelor’s/master’s in Computer Science, Statistics, Mathematics, or related fields (PhD is a plus)
• 3+ years of industry experience in ML/Data Science, ideally in large-scale recommendation systems
• Proficiency in Python and statistical tools such as NumPy, SciPy, PyTorch, or TensorFlow
• Strong experience with big data ecosystems like Spark and Hadoop
• Experience with cloud platforms such as AWS, Azure, or GCP/Vertex AI
• Expertise in algorithms for NLP, Reinforcement Learning, Time Series, and Deep Learning
• Experience deploying ML workflows and models in production systems

Preferred Qualifications

• Experience with LLMs, retrieval systems, generative models, or agentic/autonomous ML systems
• Familiarity with privacy-preserving ML and identity-less ecosystems on iOS and Android

About the Company

Glance AI is an AI commerce platform shaping the next wave of e-commerce through inspiration-led discovery. Operating in 140 countries, it transforms screens into stages for personal shopping experiences, powered by proprietary models integrated with Google’s Vertex AI.