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PranavSagar/README.md
Pranav Sagar — Backend Engineer · Distributed Systems · Java & Spring Boot Typing SVG

Portfolio LinkedIn Medium LeetCode


🧑‍💻 About Me

public class PranavSagar {

    String  company  = "Glance, InMobi Group — Bengaluru, India";
    String  role     = "SDE 1 · Backend Developer (Sept 2023 – Present)";
    String  learning = "M.Tech AI & ML @ BITS Pilani (Work Integrated)";

    String[] impact  = {
        "800K+ QPS · <30ms p95 latency · 100M+ users",
        "35–60% compute & API cost reductions",
        "Zero-downtime migrations via dual-write architecture",
        "Reusable observability framework across 5+ services",
        "90% reduction in deployment time via GKE automation",
    };

    String[] passions = {
        "Distributed Systems",
        "Event-Driven Architecture",
        "Performance Engineering",
        "Observability & Reliability",
        "MLOps & Production AI",
    };
}

⚙️ Tech Stack

Languages · Backend · Messaging

Skills

 gRPC  Protobuf  Kafka Streams


Databases · Caching

Skills

 Aerospike  ClickHouse


Data Processing

Apache Spark  PySpark  ETL Pipelines


Infrastructure · DevOps · Observability

Skills

 Helm  GKE  CI/CD  Distributed Tracing


📊 GitHub Stats


🚀 Featured Projects

🎯 Content Intelligence Pipeline — End-to-End MLOps

🌐 Live Demo · 🤖 API Docs · 🧪 MLflow · 📊 Grafana

Real-time news classifier serving fine-tuned DistilBERT at 94.64% accuracy with p95 latency of 23 ms on CPU. Production MLOps stack — streaming pipeline with at-least-once delivery, distributed caching with deduplication, drift monitoring, live dashboards, and automated CI/CD — all running on free-tier managed services with $0 recurring cost.

  • 🧠 Model: DistilBERT fine-tuned on AG News (120K articles) · 94.64% test acc · 94.65% F1 macro · MLflow tracked
  • Serving: FastAPI on HuggingFace Spaces · async lifespan · full 4-class probability breakdown · p50 19 ms, p95 23 ms
  • 🔄 Streaming: Redpanda Kafka → Redis cache (SHA-256 dedup) → SQLite · at-least-once delivery · 230 ms pipeline lag
  • 📈 Observability: Prometheus client → Grafana Alloy (pull + remote_write) → Grafana Cloud · 6-panel live dashboard
  • 🔍 Drift: weekly Evidently statistical tests (Jensen-Shannon + Wasserstein) → HTML report + MLflow on DagsHub
  • 🤖 CI/CD: ruff lint + import smoke on every push · weekly drift cron · path-filtered auto-deploy to HF Spaces
  • 📚 Docs: 12 ADRs · 15-problem build log · HLD + LLD with Mermaid sequence diagrams · layman newsroom analogy

Python PyTorch HuggingFace FastAPI Kafka Redis Prometheus Grafana Docker MLflow GitHub Actions


NLP pipeline achieving 87% accuracy using Naive Bayes, SVM, and Random Forest classifiers. Full preprocessing with tokenization, stemming, and TF-IDF. Deployed as a real-time Flask web app.

Python NLTK scikit-learn Flask

Scholarship disbursement platform eliminating 150+ km of rural travel per applicant. Built for Smart India Hackathon 2022National Runner-Up out of 1M+ participants.

Python Flask ML


🏆 Achievements

🏆 Avengers Award — Glance (InMobi) Top engineering recognition for high-impact system design
🥈 Silver Medalist — B.Tech CS, RTU CGPA 9.10 / 10.00
🥈 Smart India Hackathon 2022 National Runner-Up (1M+ participants)
📜 Microsoft Certified Azure AI & Data Fundamentals
💻 LeetCode Rating 1577 · Top 25% globally
✍️ Published on Medium Monte Carlo Simulation — most-read post

trophies

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  1. a2z_dsa_java a2z_dsa_java Public

  2. LeetCode-Curated-SQL-70 LeetCode-Curated-SQL-70 Public

    70 practice problems

    2

  3. Project-Vaani---SIH Project-Vaani---SIH Public

    Project Vani: Empowering rural beneficiaries through direct scholarship transfers, leveraging technology, and enhancing efficiency, security, and accessibility.

    JavaScript 1 2

  4. ReviewSentiments ReviewSentiments Public

    Jupyter Notebook 1