AI/ML Engineer with around 5 years of experience building scalable data pipelines, production-grade machine learning systems, and enterprise AI solutions across legal-tech, healthcare, finance, and public-sector domains. Skilled in Python, PySpark, SQL, ETL/ELT, and distributed computing, with hands-on expertise across AWS, Azure, and GCP. Experienced in developing end-to-end ML workflows including feature engineering, model training, MLOps automation, and deployment using Kubernetes, Docker, and Airflow. Proficient in building RAG and vector-search applications using GPT, LangChain, FAISS, and Pinecone. Strong background in big-data processing with Apache Spark,
Kafka, Databricks, Snowflake, and modern deep-learning frameworks like TensorFlow and Scikit-learn. Known for delivering secure, compliant (HIPAA/GDPR) AI systems that improve decision-making, reduce fraud, and automate complex legal and business workflows.
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