jegeronimo Last Checkpoint: Oct 04, 2026
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In [1]:

About

In [2]:
James Geronimo

👋 Hello! I'm James.

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🌩️ I am a software engineer at Google, working on the GKE AI Runtime team.

🧑‍🎓 I graduated from UC Berkeley with a Bachelor’s degree in Computer Science and Data Science.

💻 I enjoy building systems where users can productively interact with AI.

🎙️ Would love to chat! See the Contact tab for my email and social media profiles.

In [4]:

Move your cursor over the terrain to warp the topography.

In [1]:

Experience

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Google

Jul 2026 — Present

Software Engineer

Full-Time

GKE AI Runtime.

  • Build for everyone
In [3]:

UC Berkeley Data 100

Jun 2024 — May 2026

Lead Teaching Assistant

Part-Time

Teaching 1200+ students in the UC Berkeley's upper-division data science course, Data 100: Principles and Techniques of Data Science.

  • Teach 1200+ students in the upper-division course Data 100, covering data processing, statistical/probabilistic foundations, exploratory data analysis/visualization, feature engineering, dimensionality reduction, predictive modeling, and optimization
  • Streamline course website navigation by developing in Jekyll and automating deployment workflows through GitHub Pages
  • Lead discussion sections to 40+ students, host office hours, debug DataHub issues, and maintain general course infrastructure
In [4]:

Widget Factory

Nov 2025 — Apr 2026

Problem Design Engineer

Part-Time

Coding puzzles for frontier AI. The quality assurance division of Idler (YC S25). Backed by Y Combinator.

  • 🧩
In [5]:

Oracle

Sep 2025 — Dec 2025

Software Engineer

Contract

Engineered an AI tutor built on Oracle Cloud Infrastructure to promote active learning for UC Berkeley data science students.

  • Create an end-to-end AI tutor on Oracle Cloud Infrastructure with a RAG pipeline built on Oracle Database vectors, delivering source-grounded answers within a 2-second p50 latency SLO for 60+ concurrent users
  • Implement keyword/semantic retrieval using Autonomous AI Databases and vector embeddings for relevance
  • Construct a resilient data layer for 60+ users with usage stats, conversation logs, and insightful dashboards
  • Productionize with CI/CD (GitHub Actions), OCI autoscaling, and observability to sustain 99%+ uptime
In [6]:

Amgen

Jun 2025 — Aug 2025

AI Engineer

Internship

Created a text-to-SQL application to democratize access to marketing analytics for Amgen's Commercial Data & Analytics department.

  • Achieve 87%+ accuracy in text-to-SQL operations by building generative AI and testing frameworks in Databricks
  • Optimize Databricks SQL connection and executions by 86%+ in the worst case, reducing operations to 0–80 seconds
  • Deliver a Streamlit application optimized with caching to save 500+ hours and automate 60,000+ queries every year
  • Leverage large language models (LLMs) to automate campaign analytics across 27 brands using distributed AI agents
In [7]:

AmigoAI (SkyDeck)

Dec 2024 — May 2025

Software Engineer

Internship

Led independent projects in computer vision/optical character recognition (OCR), webscraping, and automation testing.

  • Devise and build an automated end-to-end testing framework using Playwright to detect regressions and improve test coverage
  • Engineer a robust and dynamic web scraper that mimics real-user behavior by emulating user agents, preloading consent cookies, and bypassing JavaScript-rendered content through direct HTML data extraction using Scrapy, BeautifulSoup, and Selenium
  • Scrape 1000+ data entries into JSON files for fine-tuning a custom-built LLM for standardized exam question generation
  • Construct a cross-format file processing workflow to extract text from files using PyMuPDF/Fitz and Pix2Text
  • Architect a computer vision pipeline that tracks real-time user progress to contextualize query processes in a fine-tuned LLM
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UC Berkeley Data Science Modules

Jan 2025 — May 2025

Software Developer

Part-Time

Built educational data science modules through UC Berkeley's Data Science Modules Team for El Camino College courses of varying domains.

  • Partner with four El Camino College professors to create educational data science modules teaching probability distributions, data visualization, classification, statistical modeling, and business analytics under the Data Science Modules team
  • Introduce 500+ students every semester to fundamental programming practices, statistics, and data-driven decision-making
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UCSF Abbasi Lab

Feb 2025 — Apr 2025

AI Researcher

Apprenticeship

Evaluated large language model (LLM) robustness via conversational red-teaming and multi-turn jailbreaking techniques.

  • Evaluate large language models (LLMs) robustness via red-teaming and multi-turn jailbreaking techniques under Abbasi Lab
  • Build an agentic LangChain framework to automate multi-turn LLM conversations and LLM-as-a-judge evaluations with GPT-4o
  • Customize and apply 10+ prompting goals and target strings from the MedSafetyBench dataset for attacker and target LLMs
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Universal Health Services

May 2024 — Aug 2024

AI Engineer

Contract

Constructed AutoRegressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) models for financial forecasting.

  • Achieved <18.5% and <25% average error in financial forecasting by deploying AutoRegressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) neural network models, optimized with extensive EDA and fine-tuning
  • Delivered Pyramid Analytics integration, Python script, and walkthrough video; leveraged mentorship from C-Suite executives
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UC Berkeley L&S 22

Feb 2024 — Aug 2024

Software Developer

Part-Time

Developed data science modules on Simpson's Paradox for UC Berkeley's L&S 22: Sense and Sensibility and Science.

  • Design and construct two data science modules deployed through Jupyter for the undergraduate interdisciplinary course LS 22
  • Introduce 500+ students every semester to fundamental programming practices, statistics, and data-driven decision-making
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UW School of Pharmacy

Jan 2024 — Apr 2024

AI Researcher

Apprenticeship

Leveraged Natural Language Processing (NLP) to carry out topic modeling and sentiment analysis on textual data.

  • Built and optimized a latent Dirichlet allocation model to cluster textual data, resulting in a coherence score of ~0.684
  • Leveraged natural language processing tools to enable complex analysis of textual data beyond human observation
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Organizations

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Data Science Society

Sep 2023 — May 2026

Vice President

Jan 2024 — Dec 2025

Course Director (Spring 2024), Internal Vice President (Fall 2024), and Project Manager (Fall 2025) for UC Berkeley’s first data science undergraduate student organization.

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Berkeley Engineers and Mentors

Sep 2025 — May 2026

Teaching a variety of fun and interactive STEM lessons to Berkeley / Oakland elementary school students.

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Kapatid Mentorship Program

Mar 2023 — May 2026

Connecting with my Filipino roots on campus. Shoutout OTP.

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Upsilon Pi Epsilon

Feb 2024 — May 2026

Computer Science Honors Society. Top third of Computer Science students.

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Computer Science Mentors

Sep 2023 — Dec 2024

Senior Mentor

Jan 2024 — Dec 2024

Senior Content Mentor (Spring 2024) and Senior Mentor (Fall 2024) specialized in Data Structures and Algorithms (CS 61B).

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Open Project

Feb 2023 — May 2023

Learned how to code outside of the classroom by attempting to build an NBA playoff predictor.

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Courses

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cs_courses = ["COMPSCI 370", "COMPSCI 294", "COMPSCI 194-271", "COMPSCI 194-244", "COMPSCI 189", "COMPSCI 188", "COMPSCI 170", "COMPSCI 161", "COMPSCI 70", "COMPSCI 61C", "COMPSCI 61B", "COMPSCI 61A"]
display(cs_courses)
Out[2]:
COMPSCI 370 Instructional Techniques COMPSCI 294 Computer Science Education COMPSCI 194-271 AI Education Research COMPSCI 194-244 CS Education Research COMPSCI 189 Machine Learning COMPSCI 188 Artificial Intelligence COMPSCI 170 Computer Science Theory COMPSCI 161 Computer Security COMPSCI 70 Discrete Math & Probability COMPSCI 61C Machine Structures COMPSCI 61B Data Structures & Algorithms COMPSCI 61A Computer Programs
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data_courses = ["DATA 145", "DATA 144", "DATA 140", "DATA 104", "DATA 102", "DATA 101", "DATA 100", "DATA 8"]
display(data_courses)
Out[3]:
DATA 100 Advanced Data Science DATA 145 Statistical Theory DATA 144 Data Analytics DATA 140 Probability Theory DATA 104 Data Ethics DATA 102 Inference DATA 101 Data Engineering DATA 8 Data Science
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econ_courses = ["ECON 140", "ECON 100A"]
display(econ_courses)
Out[4]:
ECON 140 Econometrics ECON 100A Microeconomics
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math_courses = ["MATH 54"]
display(math_courses)
Out[5]:
MATH 54 Linear Algebra
In [1]:

Contact

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primary_contacts = { "calendly": "calendly.com/jegeronimo/chat", "email": "jegeronimo@berkeley.edu" }
display(primary_contacts)
Out[2]:

Calendly

@jegeronimo/chat

Email

jegeronimo@berkeley.edu
In [3]:
social_profiles = { "linkedin": "@james-geronimo", "handshake": "@james-geronimo", "github": "@jegeronimo" }
display(social_profiles)
Out[3]:

LinkedIn

@james-geronimo

Handshake

@james-geronimo

GitHub

@jegeronimo
In [4]:
resume = { "name": "James Geronimo", "format": "PDF", "status": "Available" }
display(resume)
Out[4]:

Resume

James Geronimo
Simple 2 main Python 3 (ipykernel) | Idle Mem: 100.30 / 2004.08 MB
Mode: Command Ln 0, Col 0 jegeronimo 0