Information Technology
Full-Time
Dainik Bhaskar
Overview
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 :
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.
- 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.
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