Glance AI is an AI commerce platform shaping the next wave of e-commerce with inspiration-led shopping, less about searching for what you want and more about discovering who you could be. Operating in 140 countries, Glance AI transforms every screen into a stage for instant, personal, and joyful discovery, where inspiration becomes something you can explore, feel, and shop in the moment.
Its proprietary models, seamlessly integrated with Google s most advanced AI platforms, Gemini and Imagen on Vertex AI, deliver hyper-realistic, deeply personal shopping experiences across categories such as fashion, beauty, travel, accessories, home d cor, pets, and more. Designed to seamlessly integrate into everyday consumer technology, Glance AI reimagines the future of e-commerce with inspiration-led discovery and shopping.
With an open architecture built for effortless adoption across hardware and software ecosystems, Glance AI is creating a platform that can become a staple in everyday consumer technology. It partners with the world s leading smartphone makers, connected TV manufacturers, telecom providers, and global brands meeting people where they are: on mobile, smart TVs, and brand websites.
Through Glance AI s rich first-party data and unparalleled consumer access, it harnesses InMobi s global scale, insights, and targeting capabilities to create high-impact, performance-driven shopping journeys for brands worldwide. Part of the InMobi Group, a global technology and advertising leader reaching over 2 billion devices and serving more than 30,000 enterprise brands worldwide, Glance AI is backed by Google, Jio Platforms, and Mithril Capital.
What you will be doing
We are looking for a Data Scientist who can operate at the intersection of
classical machine learning
, large-scale recommendation systems
, and modern agentic AI systems
. You will design, build, and deploy intelligent systems that power Glance s personalized lock screen and live entertainment experiences. This role blends deep ML craftsmanship with forward-looking innovation in autonomous/agentic systems.
Your responsibilities will include:
Classical ML & Recommendation Systems
- 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.
Agentic Systems & Next-Gen AI
- Build and experiment with
agentic AI systems
that autonomously observe model performance, trigger experiments, tune hyperparameters, improve ranking policies, or orchestrate ML workflows with minimal human intervention. - Apply
LLMs, embeddings, retrieval-augmented architectures, and multimodal generative models
for semantic understanding, content classification, and user preference modeling. - Design intelligent agents that can automate repetitive decision-making tasks e.g., candidate generation tuning, feature selection, or context-aware content curation.
- Explore reinforcement learning, contextual bandits, and self-improving systems to power next-generation personalization.