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aseem-ai/README.md
Aseem Garg — Architecting Intelligence

$ aboutme

const aseem = {
  role: "AI/ML Engineer",
  experience: "6+ years",
  education: ["M.Sc. AI (Germany)", "B.Tech CSE (India)"],
  footprint: ["Germany", "India"],
  build_mode: "production-first",
  motto: "If it doesn’t ship, it's just a Jupyter notebook."
};

What I actually do

  • Architecting 'Zero-Touch' probabilistic decision engines.

  • Translating SOTA papers into reproducible production systems.

  • Accelerating training loops via Multi-GPU & Mixed Precision.

  • Building high-throughput Feature Stores for real-time scoring.
Status

ML Engineer

icons

🚀 Tech Stack & Tooling

🧠 AI Agents & GenAI

  • LangChain, LangGraph, Agentic Systems
  • RAG Pipelines, Llama-3, Prompt Engineering
  • Vector DBs: Pinecone, Milvus, Weaviate

🔥 Machine Learning

  • PyTorch, TensorFlow, Distributed Training (DDP)

  • Scikit-learn, XGBoost, LightGBM

  • Hugging Face Transformers

🏗 Backend & Infrastructure

  • Python (Pydantic), FastAPI
  • Docker, Kubernetes, Terraform
  • AWS: EKS, Lambda, S3

📊 Data Engineering

  • Apache Spark, PySpark

  • Event-Driven Architecture, SQL

  • Palantir Foundry

📈 Analytics & Experimentation

  • Tableau, PowerBI, Looker
  • A/B Testing, Hypothesis Testing, Statistical Inference

⚙ Core Competencies

  • System Design

  • MLOps (CI/CD for ML)

  • Algorithm Optimization

  • Technical Leadership

Focus Areas

🧠 Deep Learning

  • architectures that survive deployment

  • distillation / quantization

  • accuracy ↔ latency tradeoffs

🚀 ML Systems

  • inference at scale (online + batch)

  • monitoring, drift, incident-friendly ops

  • reproducible pipelines (CI/CD for ML)

✨ Generative AI

  • agentic workflows + RAG pipelines

  • synthetic data generation (Diffusion / GANs)

  • vector search & LLM orchestration

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