Tanmay Naik

Background

About Tanmay Naik

Machine Learning Engineer and Data Scientist with 3+ years of industry experience building scalable ML systems, real-time predictive models, and end-to-end AI pipelines across fintech, healthcare, and biometrics domains. Recent grad with a Master’s in Information Science (Machine Learning) at the University of Arizona (May 2025), with a strong foundation in deep learning, LLM fine-tuning, cloud-native deployment, and data engineering at scale. Proven track record of delivering production-ready solutions—ranging from financial market predictors to real-time biometric security systems—leveraging advanced ML techniques and distributed systems. Adept at working with large, multimodal datasets (structured, time-series, unstructured), and experienced in building and deploying LLM-based agents, reinforcement learning models, and GNN-powered recommendation systems. Skilled in Python, SQL, PySpark, and major ML libraries (TensorFlow, PyTorch, HuggingFace Transformers). Hands-on with cloud platforms (AWS, Azure), MLOps tools (Docker, MLflow, Kubernetes), and data infrastructure technologies (Airflow, Kafka, Snowflake, Redshift). Passionate about research, having led academic work on retentive networks and progressive expansion for hyperspectral image classification. Driven by a balance of technical depth and business impact, I bring a research-backed, solution-oriented mindset to every ML initiative—bridging the gap between data, insights, and real-world outcomes.