Job Summary: As an Engineering Manager – Personalization, you’ll lead the engineering efforts behind some of the most critical systems in the user journey— core recommendation infrastructure. You will own and evolve the core platforms that drive personalization at scale, powering dynamic and contextual discovery experiences across the product. You will lead and take full ownership of a cross-functional team spanning Machine Learning, Data Science, and Engineering to define and drive the future of personalized experiences. Your work will push the boundaries of innovation in multi-objective ranking, exploration strategies, and real-time inference at scale.
About the team: At JioHotstar, the Viewer Experience (VX) org is at the heart of how millions discover, engage with, and fall in love with our platform. We own the end-to-end user journey—from first app launch to daily habit loops—across Search, Personalization, Watch Experience, Interactivity, and more. We blend world-class engineering, ML, design, and data to deliver a seamless, personalized, and engaging OTT experience at massive scale. If you're passionate about building immersive, intelligent, and performant user experiences that delight a billion users, join us in shaping the future of streaming.
Key responsibilities:
Lead and scale the scale, infra & recommendations platform, owning critical systems that power retrieval, ranking, and core recommendation infrastructure for personalized experiences across the platformDrive the technical strategy and roadmap for core recommendation platforms—optimizing relevance, exploration, and user engagement through scalable, low-latency, real-time systemsArchitect backend services capable of serving hundreds of millions of users and handling massive concurrency spikes (e.g., 20x during live events) with sub-second latenciesPartner with Product, UX, and Data Science to define, build, and experiment with personalization enablers and surface-level improvements that impact discovery and engagement funnelsElevate engineering standards by championing best practices in measuring model efficacy, observability, system resilience, latency optimization, cost efficiency, and experimentation velocityOwn and improve critical personalization metrics, such as engagement uplift,coverage, and precision/recall of ranked itemsFoster a high-performance culture centered around ownership, first-principles thinking, rapid iteration, and a strong focus on end-user outcomesHire, mentor, and grow a world-class engineering team, driving career development and delivering robust, high-quality, impactful systemsCreate effective mechanisms to set goals for the team, create execution plans and track progress against those. You'll collaborate with other Developers, Program Managers, and tech support teams, in an agile environment to estimate and deliver objectives set together as a team
Skills and attributes for success:
Experienced in managing software engineering team running core ML Infrastructure and/or Big Data platforms at scaleStrong background in ML Ops, data streaming, feature stores, model deployment, or real-time processingPreferred experience includes exposure to: Recommender systems, Information retrieval, relevance, and ranking, and Large language modelsShould have experience as an individual contributor having engineered and shipped services & features at scaleExpertise in any of the programming languages (Python or Java or Golang) and hands-on architectural or distributed systems experienceProven experience designing and scaling ML infrastructure or big data platforms in productionExperience with Big Data & Real time processing systems - Spark, Spark Streaming or Flink Experience with high scale databases - MySQL, NoSQL (Scylla, Cassandra, Redis, DynamoDB)Experience using any major cloud provider (AWS, Azure, or Google Cloud) for production applicationsExperience with CI/CD processesA strong track record of project delivery for large, cross-functional, projects and bringing in and growing engineering talentExcellent written and verbal communication skills with the ability to present complex technical information clearly and concisely to a variety of audiences
Preferred education and experience:
Bachelors/master's in computer science or a related field with 8-11 years of experience in software development and 3 years of experience in managing software development team. 
