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Senior AI Infrastructure Engineer
I am a results-driven professional with over 10 years of experience in AI and HPC performance engineering. My expertise lies in optimizing HPC and Deep Learning workloads to run on NVIDIA GPUs. Throughout my career at Intel, I have contributed to the characterization and analysis of NVIDIA GPUs architecture for parallel computing, identifying performance bottlenecks, and providing recommendations to improve application performance. As a Senior AI & HPC Performance Engineer, I have conducted extensive performance analysis of workloads running on GPUs, utilizing tools such as NVIDIA Nsight to measure latency, compute, bandwidth, and power utilization. I have also developed and executed scripts for performance testing and maintained performance projection models to ensure optimal performance outcomes. In addition to my technical contributions, I have successfully led and coordinated a team of GPUs performance engineers across different projects and effectively collaborated with development teams to implement performance improvements, including code optimization. I have provided performance reports and recommendations to management and development teams, enabling informed decision-making and driving continuous improvement. My skills encompass GPUs architecture knowledge, performance profiling and analysis, proficiency in programming languages such as C and Python, familiarity with CUDA programming, and experience with ML architectures and hardware accelerators. I am well-versed in AI/DL frameworks like Tensorflow and TensorRT-LLM, and have hands-on experience with DL networks including CNN, RNN, and Transformers. Furthermore, I possess a deep understanding of GPU performance analysis tools such as Nsight-systems, Nsight-compute, and nvidia-smi. My technical proficiency extends to Linux systems, CMAKE, make tools, and maintaining Linux Ubuntu OS. I have valuable experi
San José State University
Master's degree, Computer Engineering
January 1, 1994 – January 1, 2001
NVIDIA
Senior AI Infrastructure Engineer - DGX Cloud
December 1, 2025 – Present
United States · Remote
Stealth Startup
Senior Performance/Validation Engineer
June 1, 2023 – November 1, 2025
Santa Clara County, California, United States · Hybrid
Intel Corporation
Senior AI & HPC Performance Engineer
March 1, 2008 – June 1, 2023
Santa Clara, CA
S3 Graphics
Graphics Validation Engineer.
April 1, 1997 – May 1, 2008
Fremont, California, United States · On-site
Cultural Fit Analysis
The candidate has a long and consistent career path focused on hardware and software performance, validation, and optimization, primarily in the GPU and AI/HPC domains. This specialization aligns well with a target role like ML Engineer, especially one focused on infrastructure, performance, or system-level optimization for ML. The progression from graphics validation to senior AI infrastructure engineering demonstrates adaptability and continuous learning within a highly technical field. The experience across major industry players (S3 Graphics, Intel, NVIDIA) suggests an ability to thrive in structured, high-performance environments. The lack of diverse project types outside of core performance/validation engineering might indicate a deep, rather than broad, technical interest.
Soft Skills & Operational Fit
The candidate's extensive experience in performance engineering and validation, particularly within large organizations like Intel and NVIDIA, suggests strong analytical and problem-solving skills. The descriptions imply collaboration with various engineering teams (CPU, memory, IO controller, SSD, design, driver engineers), indicating good teamwork and communication abilities. The focus on full lifecycle service engagement (design, deployment, operation, monitoring, refinement) at NVIDIA points to a proactive and ownership-driven approach. However, without specific behavioral assessment data, these are inferences based on role descriptions.