Dainik Bhaskar - Principal Machine Learning Engineer

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)