Staff Machine Learning Engineer - Recommendation Systems

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 decor, 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. Glance - An InMobi Group Company Founded in 2019, Glance is a consumer technology company that operates disruptive digital platforms including Glance, Roposo, and Nostra. Glance's 'smart lock screen' inspires consumers to make the most of every moment by surfacing relevant experiences without the need for searching and downloading apps. Glance Lock Screen is currently available on over 450 million smartphones worldwide. Roposo is a LIVE platform that is revolutionizing live experiences, through a unique, immersive, creator-led approach. Nostra is the largest gaming platform in India and Southeast Asia, offering gamers engaging ways to discover, play, watch, learn and compete. Headquartered in Singapore, Glance is an unconsolidated subsidiary of InMobi Group and is funded by Jio Platforms, Google, and Mithril Capital. For more information visit glance.com, nostra.gg, and roposo.com What should you know about joining Glance? At Glance, we walk the talk - free yourself, dream big, and chase your passion! On joining, you'll have opportunities to make an immediate impact on mission-critical projects, as you work with highly capable and ambitious peer groups.   Be rewarded for your autonomy even as you collaborate. Ideate, innovate, and inspire by leveraging bleeding-edge tech to disrupt consumer experiences.   While you work, we'll take care of nourishing your body, mind, and soul. This includes daily meals, gym, trainings, tech tools, and regular unwind sessions. Also, feel free to bring your kids - even the furry ones - to the office! What You'll Do As a Data Scientist - Recommendation Systems, you will own and drive high-impact ML systems powering personalization across Glance products. * Design, build, and deploy large-scale recommendation and personalization models using diverse, high-volume data sources. * Lead rapid experimentation--from hypothesis formulation to offline evaluation and online A/B testing--balancing speed, rigor, and business impact. * Develop and productionize end-to-end ML pipelines, including data preparation, feature engineering, model training, evaluation, and monitoring. * Partner closely with Product, Engineering, Design, UX, and Business teams to translate product goals into scalable ML solutions. * Monitor model health and performance, applying statistical techniques to ensure robustness and long-term effectiveness. * Explore and prototype new ML techniques to improve relevance, engagement, and monetization. * Act as a technical interface for stakeholders, clearly articulating trade-offs, results, and next steps. * Contribute to Glance's thought leadership through blogs, case studies, and industry conference talks. What We're Looking For Core Expectations * Deep expertise in Machine Learning, Data Science, and Recommendation Systems at scale. * Strong applied understanding of experimentation, metrics, and causal reasoning in real-world systems. * Ability to take models from idea -> prototype -> production -> business impact. Experience & Skills * 10+ years of industry experience in ML/Data Science building large-scale recommendation or personalization systems. * Hands-on experience applying techniques from ML, Deep Learning, NLP, Reinforcement Learning, Time Series, and Statistics. * Strong programming skills in Python with production-quality code practices. * Experience with big data ecosystems, especially Apache Spark. * Familiarity with cloud platforms such as AWS, GCP (Vertex AI), or Azure. * Experience operating in identity-constrained / privacy-aware environments (e.g., iOS/Android, identity-less systems) is a plus. * Excellent communication skills--able to explain complex technical ideas clearly to non-technical stakeholders. * High curiosity, strong problem-solving ability, and a bias toward learning and experimentation. Qualifications * Bachelor's or Master's degree in a quantitative field such as Computer Science, Electrical Engineering, Statistics, Mathematics, Operations Research, Economics, Analytics, or Data Science. * PhD is a plus, but not mandatory. * We value diverse academic backgrounds--great data scientists come from many disciplines. "_Glance collects and processes personal data such as your name, contact details, resume and other information that may contain personal data for the purpose of processing your application. Glance utilizes Greenhouse, a third-party platform. Please review Greenhouse's Privacy Policy to understand how the data collected from you is processed and managed. By clicking on 'Submit Application', you acknowledge and agree to the above privacy terms. 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