{"id":101355,"url":"https://alion.io/job/jio-star-engineering-manager-viewer-experience","title":"Engineering Manager - Viewer Experience","company":{"id":8901,"name":"JioStar","domain":"jiostar.com","url":"https://alion.io/company/jio-star","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":77,"open_postings":39,"ghost_share":0,"stale_share":0.897,"repost_share":0.026,"time_to_fill_p50_days":44,"computed_at":"2026-11-01T06:10:25Z"}},"role":"Leadership","role_family":"Leadership","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":34000,"max_usd":90000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":35},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Feature Store","optional":false},{"name":"Machine Learning","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Cassandra","optional":true},{"name":"CI/CD","optional":true},{"name":"DynamoDB","optional":true},{"name":"Flink","optional":true},{"name":"GCP","optional":true},{"name":"Go","optional":true},{"name":"Java","optional":true},{"name":"MySQL","optional":true},{"name":"Python","optional":true},{"name":"Recommender Systems","optional":true},{"name":"Redis","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-06-17T00:00:00Z","employer_posted_date":"2026-06-17","last_verified_at":"2026-11-01T22:44:16Z","board_verified":true,"closed_at":null,"days_open":138,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":137},"description":"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.\nKey responsibilities:\nLead and scale the scale, infra & recommendations platform, owning critical systems that power retrieval, ranking, and core recommendation infrastructure for personalized experiences across the platform\nDrive the technical strategy and roadmap for core recommendation platforms-optimizing relevance, exploration, and user engagement through scalable, low-latency, real-time systems\nArchitect backend services capable of serving hundreds of millions of users and handling massive concurrency spikes (e.g., 20x during live events) with sub-second latencies\nPartner with Product, UX, and Data Science to define, build, and experiment with personalization enablers and surface-level improvements that impact discovery and engagement funnels\nElevate engineering standards by championing best practices in measuring model efficacy, observability, system resilience, latency optimization, cost efficiency, and experimentation velocity\nOwn and improve critical personalization metrics, such as engagement uplift,coverage, and precision/recall of ranked items\nFoster a high-performance culture centered around ownership, first-principles thinking, rapid iteration, and a strong focus on end-user outcomes\nHire, mentor, and grow a world-class engineering team, driving career development and delivering robust, high-quality, impactful systems\nCreate 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\nSkills and attributes for success:\nExperienced in managing software engineering team running core ML Infrastructure and/or Big Data platforms at scale\nStrong background in ML Ops, data streaming, feature stores, model deployment, or real-time processing\nPreferred experience includes exposure to: Recommender systems, Information retrieval, relevance, and ranking, and Large language models\nShould have experience as an individual contributor having engineered and shipped services & features at scale\nExpertise in any of the programming languages (Python or Java or Golang) and hands-on architectural or distributed systems experience\nProven experience designing and scaling ML infrastructure or big data platforms in production\nExperience with Big Data & Real time processing systems - Spark, Spark Streaming or Flink\nExperience with high scale databases - 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