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ShivamKumar20-AI/README.md

Shivam Kumar

Applied AI Engineer (NLP/LLMs, classical ML)
I build and deploy machine learning and LLM applications as production‑style APIs and web apps.

Selected AI projects

Skills & stack

  • Languages: Python, SQL, TypeScript (basic)
  • ML / AI: scikit-learn, XGBoost, Random Forest, Transformers (Hugging Face), T5, DistilBERT, sentence-transformers, LangChain, RAG
  • Deep learning: TensorFlow/Keras, PyTorch (basic)
  • APIs & apps: FastAPI, Streamlit, basic Flask
  • Data: pandas, NumPy, FAISS, basic Spark
  • Dev & cloud: Docker, GitHub Actions, basic AWS/GCP, Linux

Background

  • Experience in AI governance, GDPR, ISO 27001, NIST CSF from compliance and security roles.
  • Built and deployed multiple end‑to‑end AI systems: NLP summarisation, RAG chatbots, classical ML predictors, and vision APIs.
  • Comfortable with the full pipeline: data processing → model training/fine‑tuning → evaluation → deployment → basic monitoring.

Open to work

Open to AI Engineer / ML Engineer / Applied Scientist (entry level) roles, especially in:

  • NLP / LLM applications (RAG, summarisation, classification)
  • Classical ML (tabular, forecasting, scoring models)
  • AI products in fintech, healthtech, enterprise SaaS, or AI infrastructure

Remote or UK‑based.

Focus: building real, deployable AI systems, not just notebooks.

Pinned Loading

  1. cifar10-api cifar10-api Public

    CNN image classification served as a REST API: a TensorFlow/Keras model trained on CIFAR-10 behind a FastAPI /predict endpoint.

    Python

  2. eu-ai-act-checker eu-ai-act-checker Public

    Rule-based risk classification API: screens an AI use case into EU AI Act risk tiers and returns structured, explainable JSON, with input validation, rate limiting and hashed audit logs.

    Python

  3. rag-compliance-chatbot rag-compliance-chatbot Public

    Retrieval-augmented generation over regulatory PDFs: LangChain chunking, Hugging Face embeddings, FAISS vector search and a Groq-hosted LLM, with a Streamlit interface.

    Python

  4. resume-screener resume-screener Public

    Semantic similarity with sentence-transformers: encodes a CV and a job description as embeddings and scores the match by cosine similarity, served from a FastAPI endpoint.

    Python

  5. sentiment-api sentiment-api Public

    Transformer NLP as a REST service: fine-tuned DistilBERT behind a FastAPI endpoint, returning a sentiment label and confidence score.

    Python

  6. world-cup-predictor world-cup-predictor Public

    Multi-class match-outcome prediction with XGBoost: engineered form, Elo, FIFA-ranking and head-to-head features, a time-based train/test split and an error-analysis notebook.

    Jupyter Notebook