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Machine Learning Engineer Ii - Reco Systems & Agentic Ai @ Glance

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 Machine Learning Engineer Ii - Reco Systems & Agentic Ai

Job Description

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.
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Job Classification

Industry: Software Product
Functional Area / Department: Engineering - Software & QA
Role Category: Quality Assurance and Testing
Role: Blockchain Quality Assurance Engineer
Employement Type: Full time

Contact Details:

Company: Glance
Location(s): Bengaluru

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Keyskills:   Engineer II Telecom Accessories deep learning Statistical modeling Machine learning Manager Technology E-commerce Management Monitoring

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