Ravindra Kumar
Data Scientist@Times Internet | Ex-Housing.com | RecSys | LLM | GenAI | Agentic RAG | Computer Vision | NLP | Data Science | IIT Kharagpur’21
- Role
- Data Scientist at Times Internet
- Location
- Gurugram, HR, IN
- LinkedIn followers
- 500 followers
About Ravindra Kumar
Data Scientist with 4.5+ years of experience building large-scale recommender systems and production LLM/RAG platforms. Specialized in retrieval, ranking, and agentic AI systems deployed at scale to improve user engagement and editorial workflows.Contact at:r••••••••@gmail.com
Experience
Data Scientist
Aug 2024 — Present · Noida, IN
Recommender System• Built personalized feed and push notification recommendation systems serving 1.7M+ users across iOS and Android.• Designed candidate generation using WALS matrix factorization and ScaNN-based ANN search over 50K+ articles.• Developed ranking and re-ranking models with click normalization and position bias correction to optimize CTR.• Added a sampling-based exploration strategy in production to preserve content diversity and mitigate selection bias.• Productionized ML pipelines using TensorFlow (candidate generation) and PyTorch (ranking); orchestrated via Airflow.• Delivered 120% CTR uplift with stable DAU/MAU and +15% scroll depth at < 200 ms P95 latency on FastAPI/Kubernetes.2. Editorial Judgement System• Designed an LLM-powered editorial decision layer for feed and push distribution, aligned with human editorial standards.• Extracted structured editorial signals using LLaMA-3.1-70B with SFT and QLoRA for semantic content understanding.• Integrated LLM features with ML ranking and rules, achieving additional ∼ 80% CTR uplift and ASPIRE Award recognition.3. Agentic Editorial Knowledge Retrieval System (Archive RAG)• Built agentic RAG over TOI (4M articles) using Milvus + OpenSearch hybrid retrieval with cross-encoder reranking.• Designed metadata-aware retrieval with section and temporal routing for background, latest, and timeline editorial research.• Enabled LLM inference via vLLM (LLaMA-3.1-70B) with citation-grounded generation to ensure archive-first responses.• Deployed LangGraph-based agent pipeline in production on Kubernetes, reducing manual archive lookup for editors.
Education
Chaudhari Nihal Singh Inter College, Aimi Pilibhit (UP)
Intermediate Education
2014 — 2016
Indian Institute of Technology, Kharagpur
Bachelor of Technology, Ocean Engineering and Naval Architecture
2017 — 2021
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