Computer Science graduate from Seattle University with a Data Science focus. Experienced in building software and machine learning systems, now seeking a full-time Software Engineer role.
I design and ship full-stack software and machine learning systems. My focus is on turning messy, real-world data and complex workflows into clear, reliable products that people can actually use.
- Reached 90 percent accuracy on text extraction from mobile screenshots, making flows faster and easier to test.
- Automated 7 recurring workflows with function calling and prompt design, cutting execution from minutes down to seconds.
- Captured 5,000 signups in two months by building a reliable onboarding flow that produced clean data for experiments.
- Reduced latency by 40 percent and scaled production APIs to handle 10,000 client requests per month.
- Improved response relevance by 40 percent while reducing irrelevant retrievals by 30 percent in a retrieval augmented system.
- Set clear baselines for a legal drafting pipeline with a semantic coverage score of 74.4 and a perplexity of 184.
Languages: Python, JavaScript, TypeScript, SQL, Java
Backend: FastAPI, Flask, REST, authentication and authorization, task queues
ML and AI: TensorFlow, scikit learn, LlamaIndex, vector databases such as Pinecone
Data and infra: Spark, Airflow, Docker, Firebase and Firestore, AWS and GCP
Quality: Pytest, MyPy, Ruff and Flake8, GitHub Actions
- SU Rag Chat: A full-stack retrieval augmented chatbot with clear setup and screenshots.
- AI Job Tracker Agent: A workflow that reads Gmail and writes structured entries to Google Sheets with tests and simple credentials setup.
- SSi Research: A real-time sentiment analytics platform with faster queries and a streamlined API layer.
Email: [email protected]
LinkedIn: linkedin.com/in/rohit-nagotkar
Portfolio: rxhxt.github.io/grad-portfolio