Machine Learning Engineer
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Machine Learning Engineer with 1.5+ years of experience building scalable, production-grade AI solutions. Unlike researchers who stop at the Jupyter Notebook, I specialize in End-to-End Machine Learning Engineering. I take raw data and turn it into deployed, low-latency APIs that drive business value.
My Core Competencies: Full-Stack ML: Proficient in the entire lifecycle—from data ingestion (SQL/Pandas) to model training (Scikit-Learn/PyTorch) and deployment (FastAPI/Docker).
GenAI & NLP: Architected RAG pipelines and low-latency inference engines using modern stacks (Llama 3, LangChain, Vector DBs).
System Reliability: Proven track record at Lenovo optimizing high-volume data pipelines, reducing processing time by 99% and ensuring system stability across 15 markets.
Technical Stack: Languages: Python, SQL, JavaScript.
ML & AI: Scikit-Learn, NLP, Transformers, RAG, Computer Vision.
MLOps & Cloud: Docker, Kubernetes, AWS, GitHub Actions, MLflow.
Backend: FastAPI, AsyncIO, Redis, PostgreSQL. I am methodology-agnostic: I use whatever tool solves the problem efficiently—whether that's a simple Regression model or a complex Agentic Workflow.
B.E in Aerospace Engineering from RV College of Engineering
