Software Quality Assurance Engineer - Generative AI

NVIDIA, Santa Clara, CA

September 2025 - Present

Key win: Automated KPI reporting for 260+ stakeholders, saving ~1,100 hours/year of manual work

• Developed and implemented an automated KPI reporting system using Google Apps Script, increasing data distribution efficiency to approximately 260 team members and eliminating over 1,100 hours of manual entry annually
• Collaborated with research and engineering teams to identify and address 15+ model behavior issues by translating evaluation insights into targeted prompt adjustments and dataset improvements
• Designed comprehensive evaluation frameworks and maintained rigorous documentation for generative AI outputs, ensuring consistent identification of edge cases and quality standards

Software Quality Assurance Engineer - Windows on Arm

NVIDIA, Santa Clara, CA

January 2025 - September 2025

Key win: QA point-of-contact for N1X Windows on ARM; led thermal validation workstream end-to-end

• Coordinated cross-functional validation across hardware, firmware, and software teams for Windows on ARM systems on custom N1X chipsets, serving as the QA point-of-contact bridging silicon and platform stakeholders
• Led thermal validation workstream end-to-end: built the test approach, executed sustained-workload stress runs, and reported throttling and power-profile findings to hardware engineering
• Owned I/O (USB, HDMI, DisplayPort, Audio), Wi-Fi, and Bluetooth validation test scenarios, ensuring platform stability and alignment with product release criteria

Software Quality Assurance Engineer - SimReady Studio

NVIDIA, Santa Clara, CA

May 2022 - January 2025

Key win: 60% faster testing cycles and 40% less manual work via Python automation in NVIDIA Omniverse

• Operated as the QA bridge between simulation engineering and downstream consumers of SimReady Studio assets in NVIDIA Omniverse, supporting the handoff of simulation tooling into broader DRIVE workflows
• Designed and shipped Python-based test automation that streamlined regression and daily-build validation, reducing testing cycle time by 60%
• Built automated test frameworks that cut manual testing time by an additional 40%, while enhancing CI/CD pipelines for faster feedback in Omniverse
• Authored test plans, ran daily build verification, and tracked regressions through JIRA and NVBugs, providing leadership and real-time visibility into release health

Software Quality Assurance Engineer - Autonomous Vehicles

NVIDIA, Santa Clara, CA

January 2022 - May 2022

Key win: Stronger lab-to-production handoffs through reproducible defect reporting on DRIVE stacks

• Coordinated validation of autonomous vehicle software stacks in Linux environments, executing test cases and documenting defects with reproducibility detail that accelerated engineering triage
• Improved test execution documentation and troubleshooting workflows, contributing to smoother lab-to-production handoffs between QA and development teams

Software Quality Assurance Engineer - DLSS

NVIDIA, Santa Clara, CA

August 2021 - January 2022

Key win: Validated DLSS titles across diverse configs and hardware; documented partner integration issues

• Validated gaming titles integrating NVIDIA DLSS, testing AI-driven upscaling behavior across diverse application configurations and hardware profiles
• Documented integration challenges and partner-facing issues, supporting the developer experience for studios adopting the technology

Key win: Led Oakland police-fairness research (RUMBA) with Python, Pandas, and Jupyter on large datasets

• Selected for the Research for Undergraduates on the Mathematics of the Bay Area (RUMBA) program; led a police fairness research project for the City of Oakland using statistical analysis
• Cleaned and processed large datasets in Python and Pandas, building analytical models in Jupyter to surface patterns—foundational experience in the data side of the ML lifecycle

Software Engineering Intern - Robotics

NVIDIA, Santa Clara, CA

January 2020 - August 2020

Key win: Python scenario automation in Isaac Sim and Omniverse, expanding robotics test coverage

• Contributed to NVIDIA Isaac Sim, the industry's first robotic AI development platform with simulation capabilities
• Authored Python scripts to programmatically generate simulation scenarios in Omniverse, expanding test coverage for robotics workflows
• Reviewed peer code and debugged simulation issues across the Isaac Sim stack, partnering with engineering to triage root causes and validate fixes ahead of release
• Reviewed release documentation for accuracy and completeness prior to ship

Technical Program Management Intern - Autonomous Vehicles

NVIDIA, Santa Clara, CA

August 2016 - January 2020

Key win: Owned ADAS multi-sensor dataset pipeline and weekly executive reporting for 3+ years

• Owned end-to-end program coordination for the Autopilot (ADAS) multi-sensor dataset pipeline—tracking dataset inventory, monitoring active-use data, scoping new acquisitions, and aligning data supply with DNN training timelines
• Authored enforceable data specifications for the ADAS program—annotation guidelines, tooling instructions, and dataset requirements—translating research model needs into clear specs for the labeling workforce
• Managed the labeling workforce end-to-end: onboarding, guidelines training, delivery tracking, and quality iteration loops for multi-sensor ADAS datasets
• Performed QA across the AI/ML lifecycle—data labeling, model output verification, and integration validation for ADAS and self-driving vehicle systems powered by Deep Neural Networks
• Delivered weekly executive reports to stakeholders and leadership covering data supply/demand, labeling throughput, quality metrics, tooling health, and risks