About

I’m Tino Trangia — a software engineer and data scientist working at the intersection of ML research and production systems. My research interests are interpretable ML, LLM reasoning and evaluation, AI alignment and safety, and applied NLP.

Education

University of California, San Diego — M.S. Data Science · GPA 3.97
Sep 2024 – Jun 2026 · La Jolla, CA

• Coursework: Probability & Statistics, Machine Learning, Databases, ML Systems, Deep Learning, NLP, AI safety, Interpretable ML, Trustworthy ML, NLP, Data-Centric AI

University of California, Berkeley — B.S. Electrical Engineering and Computer Science · GPA 3.76
Aug 2019 – May 2023 · Berkeley, CA

• Coursework: Data Structures, Algorithms, Operating Systems, Computer Architecture, Distributed Systems

Experience

Graduate Reader — UC San Diego
Jan 2026 – Mar 2026 · La Jolla, CA

• Assisted in teaching data science algorithms (DSC 206) to 70+ graduate students.
• Proctored exams and evaluated student assignments, providing written feedback to reinforce conceptual understanding of topics such as graph clustering, gradient descent, and neural networks.

Software Engineer — FabricFeed
May 2023 – Dec 2025 · Sacramento, CA

• Built and deployed a natural-language reporting agent that composes multi-step SQL query plans against a production schema, cutting report turnaround from an hour of manual work to 10 minutes for non-technical users.
• Built an inventory management and analytics dashboard (Django, PostgreSQL, Next.js) tracking textile waste across dozens of streams, writing SQL queries that surfaced recycling trends and inefficiencies for operational decisions.
• Designed and built a full-stack ERP application for a startup MVP, owning PostgreSQL schema design, REST API design, and Dockerized deployment with GitHub Actions CI/CD, AWS ECS, and Vercel.

Academic Intern, Data 8: Foundations of Data Science — UC Berkeley
Aug 2022 – Dec 2022 · Berkeley, CA

• Assisted in teaching introductory data science concepts to 30+ students in section.
• Reinforced concepts such as sampling, regression, A/B testing, and causality.

Research Assistant — Space Sciences Laboratory
Sep 2020 – May 2022 · Berkeley, CA

• Developed a Python application for isotope mapping from 10+ GB neutron imaging data cubes, parallelizing archive decompression across a thread pool to cut startup time by 70%, and added caching to speed up repeat analyses.
• Built automated test and visualization pipelines for space-borne sensor data, replacing manual tests and data entry.

Academic Intern, CS 61B: Data Structures — UC Berkeley
May 2021 – Dec 2021 · Berkeley, CA

• Helped students complete lab assignments and major Java-based projects.
• Reinforced concepts in inheritance, trees, graph theory, and sorting.

Leadership

President, Engineering Student Council — UC Berkeley

• Represented 50+ engineering clubs; spearheaded implementation of a comprehensive set of policies for fair recruitment, financial accountability, and safety; speaker at major donor events.

Skills

Programming Languages: Python, SQL, Java, JavaScript, TypeScript, Golang, R, C#, C++, C

Technologies & Frameworks: Git, AWS, Docker, FastAPI, Django, Next.js, React, PostgreSQL, Neo4j, PyTorch, TensorFlow, JAX, Ray, Spark, NumPy, HuggingFace, Pandas, scikit-learn, LangChain, LangGraph, Pydantic, HTML

Concepts: RAG, LoRA fine-tuning, agentic AI, reinforcement learning, context engineering, LLM evaluation