Aditya K.

About Aditya K.

I\'m a Machine Learning Engineer with 4+ years of software engineering experience now focused on building production grade AI and Generative AI products. My background as a full stack engineer at Intuit and Wipro taught me what it takes to ship software that 15K+ daily users actually depend on and I bring that same discipline to ML clean data pipelines, reproducible training, monitored deployments, and measurable business impact. What I specialize in Generative AI & LLM applications RAG systems, fine tuning, prompt engineering with LangChain & Hugging Face, Machine Learning, PyTorch, scikit learn, TensorFlow classification, regression, NLP, recommendation models, MLOps Docker, Kubernetes (CKA-certified), AWS (Certified Developer Associate), CI/CD for ML Data Engineering, Python, SQL, Pandas, NumPy, ETL pipelines, feature engineering Built and maintained a full stack analytics platform supporting daily users. Reduced healthcare reporting query response via SQL indexing and execution plan tuning. Hold AWS Developer Associate, Certified Kubernetes Administrator (CKA), Oracle Java 17, and Microsoft Python Developer I\'m actively pursuing AI/ML Engineer, Generative AI Engineer, and Machine Learning Engineer roles where I can ship LLM powered products end-to-end from prototype to production. Open to full time opportunities (US, remote/hybrid). Reach me at a••••••••@gmail.com or DM here.

Experience

1. Software Engineer

   Intuit

   Jun 2024 — Present · New York, NY, US

   Designed and deployed Python-based ML and data services powering financial product features used by millions of Intuit customers, integrating with internal data platforms and downstream APIs.Built and maintained scalable backend services in Python and Java (Spring Boot), deployed via Docker and Kubernetes on AWS, supporting high-availability production workloads.Developed data pipelines and feature engineering workflows to support model training and evaluation, improving experimentation velocity for ML teams.Implemented observability, logging, and CI/CD automation that reduced deployment cycle time and improved release reliability.Partnered with data science, product, and platform engineering teams to translate ML prototypes into production ready services with clear SLAs and monitoring.Contributed to code reviews, design discussions, and technical documentation, raising engineering quality standards across the team.

Education

• Montclair State University

  Master's degree, Computer Science