Larry Mai

Software Engineer

I specialize in building ML and full-stack systems.

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Experience
Apr 2025 – Apr 2026
Software Engineer (AI)
Mercor · Remote
  • Architected end-to-end data pipelines that ingest 1,000+ open-source GitHub repositories and emit SWE-bench-style training instances, automating Docker environment setup, commit-pinned dependency resolution, and isolated test execution for reproducible LLM training and evaluation.
  • Wrote pytest verification harnesses reaching 90–100% line coverage on target issues, producing high-fidelity pass/fail reward signals used to fine-tune agentic coding models at frontier AI labs.
  • Curated and annotated issue, gold-patch, and test training triples across heterogeneous codebases, debugging flaky tests, dependency conflicts, and historical build breakage at scale.
Sep 2022 – Aug 2024
Software Engineer I (Wireless)
Corning (now Airspan Networks) · Milpitas, CA
  • Engineered Layer 3 networking stack features in C++ for 5G radio access networks, scaling to support more than 1 million users.
  • Designed system alarms and call performance reports in C that decreased network downtime by 18%, and implemented LTE subscriber redirection that improved handover success rates by 22%.
  • Managed and optimized 15+ developer environments and servers (WRCP, Supermicro), reducing configuration time by 40% and cutting network setup time from 3 days to 4 hours.
  • Created and executed 200+ automated test cases for Qualcomm and Samsung chipset compatibility, increasing test coverage by 35% and identifying 28 critical integration issues before production.
  • Successfully integrated 3 new vendor 5G core systems into existing network architecture, maintaining 99.9% service availability during transition and reducing operational costs by 15%.
Sep 2021 – Jun 2022
Embedded Software Engineer
Laritech · Goleta, CA
  • Designed and programmed C++ firmware for an STM32L072 microcontroller using I2C, UART, GPIO, and ADC interfaces to collect real-time environmental data from seven peripherals.
  • Implemented LoRaWAN communication over the 915 MHz spectrum to transmit sensor data packets from distributed field nodes to a centralized ESP32 gateway across distances of up to 40 meters.
  • Led PCB design across two hardware revisions and successfully deployed the resulting sensor network.
  • Developed machine learning models to analyze sensor-network data for weather-pattern modeling.
Jun 2021 – Sep 2021
Software Engineering Intern
Stealth Startup · San Francisco, CA
  • Built a Django and React B2B web application to provide precise investment analytics to over 10 companies.
  • Implemented Python-based fuzzy search algorithms with over 90% accuracy for financial risk analysis and recommendations.
  • Achieved 99.9% uptime after migrating codebase to an AWS serverless architecture including AWS Lambda, EC2, and S3.
  • Utilized MySQL and AWS Aurora DB for data querying and ran machine learning models with over 90% accuracy to analyze over 100 trends in venture capital revenue and growth.
Sep 2019 – Dec 2019
Software Engineering Intern
Piedmont Racing Limited · Santa Barbara, CA
  • Created Python scripts to transform MySQL data into structured spreadsheet formats for efficient analysis of sports tracking data.
Jun 2018 – Aug 2018
IT Development Intern
AGS Inc · San Francisco, CA
  • Developed a Python web scraping tool that automated data collection for 300+ engineering projects.
Projects
2026
MMA LLM
Built and trained a 35M-parameter Llama-style autoregressive language model from scratch in PyTorch, implementing multi-head attention, RoPE embeddings, RMSNorm, and SwiGLU activations. Trained a custom 16k-vocabulary BPE tokenizer, completed general pretraining on 8M tokens, and continued domain pretraining on verbalized UFC fight data. The model generalized to held-out prompts and generated syntactically correct, contextually coherent fight summaries.
PyTorchLlamaBPERoPERMSNormSwiGLU
2025
LogMyBeans.com
Full-stack web app for espresso enthusiasts to catalog machines and grinders, track beans by roast date, origin, and process, and log shots through a schema that links beans, equipment, grind settings, and results.
Next.jsTypeScriptTailwind CSSPostgreSQLGoogle OAuth
2025
Ochtagon.com
Full-stack UFC pick-em application used by hundreds of users to make predictions, track results, and score points in real time. Built a live scoring engine and idempotent ingestion pipeline that handle fighter replacements, cancellations, weight-class changes, no-contests, and late result corrections without disrupting active picks.
FastAPINode.jsTailwind CSSJavaScriptPostgreSQLDockerRedis
2025
Personal Portfolio Website
Personal website (this one) showcasing my work and skills as a software engineer.
Next.jsNode.jsTailwind CSSJavaScriptTypeScript
2025
Monitoring Application
Command-line application that integrates with public and unofficial APIs to monitor real-time availability for more than 1,000 products across Target, Costco, Best Buy, and other major retailers.
PythonAPI
2022
Geographical Environmental Module
Hardware and software device used for external environmental monitoring.
C++PythonArduinoEagle
2019
Budgeting Chrome Extension
Created a full stack chrome extension that helps users budget their money.
HTMLCSSJavaScriptChrome Extension API
2019
Uber Voice Recognition App
Caltech Hackathon 2019 Project. Voice recognition 2FA for Uber drivers.
PythonGoogle APIDialogflow
2020
Google to Spotify
SB Hacks 2020 Web Application. Spotify playlist generator based on user's emotional state.
Node.jsGoogle Vision APISpotify API
Education
Jan 2026 – May 2028
M.S. in Computer Science · GPA: 4.0
Georgia Institute of Technology
Aug 2018 – June 2022
B.S. in Computer Engineering
University of California, Santa Barbara
Research
May 2026 – Present
Neural Network For Memory Trace Compression
AI Graduate Researcher under Dr. Jeffrey Young
  • Showed that low address-delta reconstruction loss can still produce failure-scale cache hit-rate errors because cumulative integration breaks cache-block reuse identity.
  • Redesigned the proxy generator around logarithmically binned reuse distance, stateful workload conditioning, and LRU-stack replay.
  • Produced a 565,681-byte deployment package whose largest observed in-sample hit-rate error was 0.0037807 across five evaluated workloads.
Read full technical report
2018 – 2020
Atmospheric Water Generator
UCSB CSEP Capstone Project
  • Developed and programmed internal and external temperature and humidity sensors in C++ to monitor environmental conditions for water generation.
  • Designed and implemented a real-time data logging system using ISRs and RTOS to capture and analyze day–night cycle patterns affecting water yield.
  • Engineered circuit designs to power and control key system components, including cooling fans, power regulation modules, and a water quality sensor for cleanliness monitoring.
Skills & Technologies
Languages
PythonTypeScriptJavaScriptC++JavaSQLGoHTMLCSS
Areas
5G WirelessMachine LearningAILLM TrainingReinforcement LearningFull-Stack DevelopmentEmbedded SystemsReal-Time SystemsCI/CDQA Testing/AutomationDevOps
Tools
PyTorchNumPyPandasscikit-learnOpenCVMATLABFastAPIReactNext.jsNode.jsExpressFlaskSupabasePostgreSQLRedisGitDockerLinuxJenkinsKubernetesAWSGCPAzureSTM32RTOSISRLoRaWANI2CUARTGPIOADCPCB Design
Built with Next.js & Tailwind CSS by Larry Mai.