Machine Learning Engineer III - Recommendation Systems
- Glance
- 6 - 11 years
- Bengaluru
- 10 days ago
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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 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; 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 modelling.
- 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.
Cross-functional impact
- Collaborate with Designers, UX Researchers, Product Managers, and Software Engineers to integrate ML and GenAI-driven features into Glance s consumer experiences.
- Contribute to Glance s ML/AI thought leadership blogs, case studies, internal tech talks, and industry conferences.
- Thrive in a multi-functional, highly collaborative team environment with engineering, product, business, and creative teams.
- Plus: Interface with stakeholders across Product, Business, Data, and Infrastructure to align ML initiatives with strategic priorities.
We are seeking candidates with deep expertise in ML, recommendation systems, and a strong appetite for building agentic AI systems.
You should have experience with:
- Large-scale ML and recommendation systems (collaborative filtering, ranking models, content-based approaches, embeddings).
- Classical ML and deep learning techniques across NLP, sequence modelling, RL, clustering, and time series.
- Experience in deploying ML workflows/models in production system
- Big data processing (Spark, distributed data systems) and cloud computing.
- Designing end-to-end ML solutions from prototype to production.
- Plus: Building or experimenting with LLMs, generative models, and agentic AI workflows (e.g., autonomous evaluators, self-improving pipelines, automated experiment agents).
We value curiosity, problem-solving ability, and a strong bias toward experimentation and production impact.
Our team includes engineers, physicists, economists, mathematicians, and social scientists a great data scientist can come from anywhere.
Qualifications
- Bachelor s/master s in computer science, Statistics, Mathematics, Electrical Engineering, Operations Research, Economics, Analytics, or related fields. PhD is a plus.
- 6+ years of industry experience in ML/Data Science, ideally in large-scale recommendation systems or personalization.
- Experience with LLMs, retrieval systems, generative models, or agentic/autonomous ML systems is highly desirable.
- Expertise with algorithms in NLP, Reinforcement Learning, Time Series, and Deep Learning, applied on real-world datasets.
- Proficient in Python and comfortable with statistical tools (R, NumPy, SciPy, PyTorch/TensorFlow, etc.).
- Strong experience with the big data ecosystem (Spark, Hadoop) and cloud platforms (Azure, AWS, GCP/Vertex AI).
- Comfortable working in cross-functional teams.
- Familiarity with privacy-preserving ML and identity-less ecosystems (especially on iOS and Android).
- Excellent communication skills with the ability to simplify complex technical concepts.
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Job Classification
Industry: Software ProductFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Machine Learning EngineerEmployement Type: Full timeContact Details:
Company: GlanceLocation(s): Bengaluru+ View Contact
Keyskills: Computer science Telecom Accessories Cloud computing Prototype GCP Machine learning Analytics Python Android
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