# Nitin Datta Movva > Software Engineer (GenAI / ML) | LLM Systems, RAG, LangGraph | FastAPI, AWS | M.S. Data Science @ SJSU Location: San Jose, California, United States Profile: https://flows.cv/nitindattamovva I’m a Software Engineer focused on GenAI and Machine Learning systems, with an M.S. in Data Science from San Jose State University, building production-ready platforms that combine LLMs, retrieval, and modern web infrastructure. At Cloudely, I architected and shipped a hybrid RAG system using BM25 (Elasticsearch) and dense embeddings (OpenAI Ada-002, E5-large) with bge reranking and Reciprocal Rank Fusion, improving retrieval precision by 35% in real-world usage. I led end-to-end platform modernization—migrating backend services from Node.js to FastAPI, rebuilding the frontend with Next.js, Tailwind, and shadcn/ui, and setting up GitHub-based CI/CD pipelines—resulting in a 40% increase in development velocity. I also built a LangGraph-based multi-agent orchestration layer to translate natural language into automated application workflows. Previously at Helix Tech, I engineered HIPAA-compliant GenAI pipelines for healthcare applications. I improved LLM accuracy by 20% using RLHF (GRPO, DPO) on clinical QA datasets and fine-tuned LoRA adapters with dynamic routing to scale model performance across multiple healthcare subdomains. At Intel, I worked as a Machine Learning Intern developing scalable ML systems (XGBoost, CatBoost, Random Forests) for defect detection and yield optimization, delivering measurable production impact, cost savings, and significant reductions in manual analysis through automation and internal tooling. I’m strongest at the intersection of software engineering and applied AI—designing APIs, data pipelines, and user-facing systems that make GenAI reliable in production. Core stack: Python, FastAPI, PyTorch, Hugging Face, LangGraph, vLLM, AWS, PostgreSQL, Redis, Elasticsearch, Next.js. I’m actively exploring Software Engineer (GenAI / AI Platform), Applied AI Engineer, or ML Engineer roles where I can build scalable, high-impact AI-powered systems. ## Work Experience ### Software Engineer @ Cloudely, Inc Jan 2025 – Present | San Jose ● Architected Hybrid RAG pipeline combining BM25 (Elasticsearch) and dense embedding retrieval (OpenAI Ada-002, E5-large, bge-reranker) with Reciprocal Rank Fusion, improving retrieval precision and contextual grounding by 35% ● Led a full-stack migration from Node.js to FastAPI and React to Next.js with Tailwind & shadcn UI, establishing CI/CD pipelines on GitHub and improving development speed and productivity by 40% ● Built a LangGraph-based multi-agent orchestration layer for retrieval, validation, and workflow generation, empowering users to automate app creation through natural language ### Open Source Developer @ AmpyFin Jan 2025 – Present | San Francisco, California, United States Modernized the platform by refactoring 4,500+ lines of legacy code into typed, well-documented modules; implementing CI/CD to auto-lint/test/scan every PR; & parallelizing core algorithms with multiprocessing to cut execution time by 90% ### Software Engineer @ Helix Tech IT Services Jan 2024 – Jan 2025 | San Jose, California, United States ● Orchestrated HIPAA-compliant data pipelines across diverse healthcare sources, ensuring 100% privacy for LLM training ● Boosted base LLM performance by 20% through RLHF on clinical question–answer pairs, leveraging GRPO and DPO techniques to enhance factual accuracy, reasoning consistency, and domain-specific reliability ● Fine-tuned specialized LoRA adapters on the aligned model and implemented dynamic adapter routing, improving question-answering accuracy and contextual adaptability by 30% across healthcare subdomains ### Machine Learning Engineer @ Intel Corporation Jan 2023 – Jan 2023 | Santa Clara, California, United States ● Engineered & optimized scalable Machine Learning models such as XGBoost, CatBoost, Random Forests to identify defects resulting in a yield improvement exceeding 0.3% ● Communicated model insights to stakeholders using Explainable AI techniques leading to company-saving of over $100,000 ● Deployed web app for automated model training, resulting reduction of more than 50% in manual work hours ● Architected a suite of scalable data loaders transforming raw feeds into analytics-ready datasets, unblocking 4+ downstream teams & 20+ engineers ### Graduate Research Assistant @ San Jose State University Jan 2022 – Jan 2022 | San Jose, California, United States I worked on applying machine learning to identify defects in neuromorphic circuits. I trained and optimized classification models to detect defect patterns such as line, ring, and other structural anomalies, improving accuracy and reliability in defect detection. ### Data Science Intern @ II-VI Incorporated Jan 2022 – Jan 2022 | San Jose, California, United States ● Built ETL pipeline using Airflow & AWS S3 to load 3 years’ worth network data achieving 20% performance improvement ● Forecasted to predict network usage with models such as ARIMA, SARIMAX, ConvLSTM achieving RMSE of 0.09 ### Data Science Intern @ Moglix Jan 2019 – Jan 2021 | India • Led a 3-person initiative to optimize industrial product recognition, engineering ResNet/EfficientNet vision classifiers and data/training improvements to reach 86% accuracy. • Built and integrated description-based models (XGBoost, Gradient Boosting, KNN) with vision outputs, improving robustness and reducing misclassification across product categories ### Data Science Intern @ Tata Communications Jan 2018 – Jan 2019 | Chennai, Tamil Nadu, India ● Developed data-preprocessing pipeline and other small-scale pipelines to analyze network data using Pandas ● Created visualizations to generate insights from data using Seaborn and Matplotlib ### Member @ Club Gen-Y Jan 2018 – Jan 2018 | Chennai Area, India ## Education ### Master's degree in Data Science San José State University ### Bachelor of Technology - BTech in Computer Science SRM IST Chennai ## Contact & Social - LinkedIn: https://linkedin.com/in/nitindatta8 - Portfolio: https://nitindatta-portfolio.vercel.app/ --- Source: https://flows.cv/nitindattamovva JSON Resume: https://flows.cv/nitindattamovva/resume.json Last updated: 2026-04-10