Hello, I'm

Beatriz Santos

Software Quality Assurance Engineer

Results-driven QA Engineer with 9+ years of experience in software testing, automation, and quality assurance. Passionate about delivering high-quality software through comprehensive testing strategies and automation.

Windows on ARM Testing
Autonomous Vehicle Testing
Test Automation
Performance Testing
Gaming Technology

Career Objectives

Project Management
Quality Assurance
Test Automation
Hardware Validation
Cross-platform Testing
Framework Development

Key Achievements

  • Improved testing efficiency by 60% through Python automation
  • Successfully validated Windows on ARM systems with N1X chipsets
  • Contributed to 5+ major NVIDIA projects across autonomous vehicles and gaming
  • Developed automated test frameworks reducing manual testing time by 40%
  • Enhanced CI/CD pipelines for faster feedback cycles in NVIDIA Omniverse
  • Maintained test coverage across critical system components

Experience

Software Quality Assurance Engineer

NVIDIA, Santa Clara, CA

September 2025 - Present
  • Evaluated the quality of generative AI outputs by systematically testing prompts, verifying factual correctness, and documenting clear rationales for why responses met or failed quality standards
  • Reviewed AI-generated outputs against source data and business rules, flagging issues and providing clear guidance to improve model behavior
Generative AI Quality Evaluation Testing

Software QA Engineer - Windows on ARM

NVIDIA

April 2025 - September 2025
  • Performing comprehensive QA testing for Windows on ARM systems powered by custom N1X chipsets
  • Validating functionality of all system I/O ports (USB, HDMI, DisplayPort, Audio)
  • Executing wireless connectivity testing for Wi-Fi and Bluetooth
  • Leading thermal testing and monitoring efforts with hardware team
Windows on ARM N1X Architecture Hardware Testing

Software QA Engineer - DRIVE Simulation

NVIDIA

May 2022 - April 2025
  • Collaborating with engineering teams for SimReady Studio in NVIDIA Omniverse
  • Developed automated testing solutions using Python, improving efficiency by 60%
  • Participating in test plan development and regression monitoring
  • Maintaining comprehensive issue tracking via JIRA and NVbugs
Python NVIDIA Omniverse CI/CD JIRA

Software QA - AV

NVIDIA

January 2022 - May 2022
  • Supported testing of autonomous vehicle software in Linux environment
  • Troubleshot execution challenges with thorough documentation
  • Executed test cases and documented software defects
Linux NVIDIA DRIVE Bug Tracking

Student Researcher

California State University - East Bay

August 2021 - March 2022
  • Selected for the RUMBA program (Research for Undergraduates on the Mathematics of the Bay Area)
  • Conducted research project on Police Fairness in the City of Oakland using statistical analysis
  • Cleaned and processed large datasets using Python and Pandas for data analysis
  • Developed analytical models in Jupyter Notebooks to identify patterns and insights
  • Collaborated with faculty, graduate students, and Bay Area groups on mathematical research
Python Pandas Jupyter Notebooks Data Analysis RUMBA Program

Software QA - DLSS

NVIDIA

August 2021 - January 2022
  • Conducted validation of gaming titles implementing NVIDIA's DLSS technology
  • Documented and analyzed application integration challenges
  • Implemented rigorous testing methodologies for DLSS optimization
DLSS Game Testing Performance Analysis

Software Intern, Robotics

NVIDIA

January 2020 - August 2020
  • Contributed to NVIDIA Isaac Sim development for robotic AI simulation
  • Worked on robot models and task simulations showcased at GTC 2020
  • Supported the industry's first robotic AI development platform with simulation capabilities
NVIDIA Isaac Sim Robotics AI Simulation

Engineering Intern, Autonomous Vehicles

NVIDIA

August 2016 - January 2020
  • Performed QA for Advanced Driver Assistance System (ADAS) and self-driving vehicles using Deep Neural Networks (DNN)
  • Created and maintained product requirement documentation for Autopilot (ADAS) including labeling guidelines, tool instructions, and technical product overview
  • Trained image labelers using labeling guidelines
  • Contributed to NVIDIA's self-driving car demo showcased at CES 2017
ADAS Deep Neural Networks Autonomous Vehicles Image Labeling

GitHub Repos

View All Projects

Areas of Interest

Advanced Testing
AI/ML
Test Infrastructure
Simulation
Autonomous Systems
Gaming Technology

Get In Touch

Interested in working together? Have a question or project in mind? Feel free to reach out!