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Job Description We're building the most personalized and intelligent news experiences for Indias next 750 million digital users. As our Principal Machine Learning (ML) / Personalization Engineer, you will : Architect and deploy ML-based personalization systems for our suite of digital news products, including recommender systems for content ranking, homepage personalization, push notification targeting, and audience segmentation. Collaborate closely with editors, product managers, and analysts to integrate machine learning into the editorial workflowmaking content creation, packaging, and distribution smarter and audience-aware. Analyze user behavior and content consumption patterns using large-scale datasets to build user understanding models and inform personalization strategies. Own the end-to-end ML pipeline: from data acquisition, feature engineering, model training & evaluation, to deployment and real-time inference. Drive experimentation culture: lead A/B testing and iterative optimization of recommendation and ranking models. Stay on top of global trends in personalization, news AI, large language models (LLMs), and recommendation systems, and bring best-in-class solutions to our stack. Who You Need To Be Bachelors or Masters degree in Computer Science, Data Science, Statistics, or a related field. 812 years of experience in machine learning, ideally in recommendation systems, personalization, or search relevance. Strong experience with Python and ML frameworks like TensorFlow, PyTorch, or Scikit-learn. Hands-on with recommendation engines (collaborative filtering, content-based, hybrid models) and vector similarity models. Experience with real-time data processing frameworks and deploying models in production. Solid understanding of SQL and data platforms (e.g., Snowflake, BigQuery, or Redshift). Exposure to BI tools (Metabase, Looker, Tableau) is a plus. Comfortable navigating ambiguous, fast-paced environments and leading cross-functional initiatives. Excellent communication and collaboration skillsable to explain complex ML concepts to non-technical stakeholders. (ref:hirist.tech) Show more Show less
