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vinodseshadri/README.md

Hi there 👋, I'm Vinod Seshadri

Machine Learning | Data Science | GenAI & MLE Leader

I have over 20 years of experience in the tech industry, with a deep focus on Production AI Systems and Machine Learning Engineering for the last 8+ years. Currently, I serve as a Senior Machine Learning Architect at Tiger Analytics, leading the deployment of Agentic AI and high-scale GenAI solutions.

My expertise lies in building Autonomous Agent Systems, Enterprise MLE Platforms, and Serverless AI Architectures that process millions of records at scale.

🚀 Side Projects

I have open-sourced several key projects that demonstrate scalable AI architectures and industrial anomaly detection:

1. AWS Serverless Resume Pipeline

A fully cloud-native, event-driven document processing system.

  • Tech: AWS Lambda, Textract, Comprehend, Cognito, S3, SQS.
  • Highlight: Implements a serverless microservices architecture to extract insights from resumes, featuring a custom Chat UI integrated with AWS Lex for interactive querying. Matches my professional work in Conversational AI and Cloud Architecture.

2. Deep Anomaly Analytics Engine

Advanced industrial monitoring for time-series sensor data.

  • Tech: Keras (LSTM Autoencoders), MongoDB, Python, Plotly.
  • Highlight: detects anomalies in real-time sensor streams from PLCs. This project reflects my professional experience in Univariate/Multivariate Time Series Analysis and IoT Anomaly Detection.

3. NLP Resume Parser

Privacy-first Named Entity Recognition engine.

  • Tech: SpaCy, Flask, PDFMiner.
  • Highlight: A custom-trained NER model for high-precision extraction of skills and certifications, designed for secure, local processing of sensitive candidate data.

Open source contributions

💡 Patents & Innovations

  • Patent US10725899B2: Method and system of performing automated exploratory testing of software applications using reinforcement learning.
  • Book Chapter: Intelligent Research Laboratory - AI/ML Methods for Chemists (part of "Artificial Intelligence for Multimedia Information Processing").
  • Innovation: Architected a high-scale GenAI Medical Record Summarization platform processing 2.5M+ records/month, projecting $2.3M in savings.

🛠️ Technical Arsenal

Domain Technology Stack
Agentic AI & GenAI Google ADK, AWS Bedrock, Multi-Agent Systems, RAG, Prompt Engineering, LLM-as-a-Judge, MCP
Data Science & ML Python (Advanced), PyTorch, Pandas, LightGBM, Deep Learning, NLP, Information Retrieval
Cloud & MLE AWS (Lambda, Sagemaker, Bedrock), Airflow, MLFlow, Docker, Kubernetes, GitHub Actions (CI/CD)
Data & Infra Snowflake, Redis, Splunk, HA/DR Architecture, CloudFormation, SQL

Pinned Loading

  1. adk-python adk-python Public

    Forked from google/adk-python

    An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

    Python

  2. aws-serverless-resume-pipeline aws-serverless-resume-pipeline Public

    JavaScript

  3. deep-anomaly-analytics-engine deep-anomaly-analytics-engine Public

    Python

  4. nlp-resume-parser nlp-resume-parser Public

    NLP based resume parser

    Python

  5. snowflake-connector-python snowflake-connector-python Public

    Forked from snowflakedb/snowflake-connector-python

    Snowflake Connector for Python

    Python