We are looking for an ambitious, hands-on Machine Learning Engineer to build and scale intelligent algorithms that power our core consumer internet platform. Based out of our Hyderabad or Gurgaon technology centers, you will work closely with product, data, and engineering teams to design recommendation systems, personalization models, and predictive user-behavior pipelines. You will take machine learning models from exploratory data analysis all the way to production microservices in a high-energy, collaborative office environment.
Key Responsibilities & Detailed Breakdown:1. Model Development & Training
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Design, train, and evaluate machine learning models (ranging from gradient boosting and team-oriented filtering to deep learning and NLP frameworks) to drive user engagement and personalization.
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Build robust feature engineering pipelines using large-scale user interaction data, clickstream logs,
and transactional records.
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Continuously monitor model performance in production, detect feature/concept drift, and retrain models to ensure high accuracy and relevance.
2. Productionization & MLOps
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Translate experimental code (Jupyter notebooks) into clean, modular, and scalable production-ready Python code.
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Deploy models as low-latency REST APIs or microservices using FastAPI, Docker, and container orchestration platforms.
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Optimize algorithmic inference latency to ensure real-time responsiveness for millions of concurrent platform users.
3. Cross-Functional Collaboration & Innovation
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Participate in daily in-office standups, sprint planning sessions, and architecture reviews with backend engineers and product managers.
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Collaborate with data engineers to streamline data ingestion, storage, and feature store updates.
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Run rapid test-and-learn experimentation frameworks (A