Senior Software Engineer – Local AI

NVIDIA

Senior Software Engineer solving client-side AI challenges on Windows and Linux PCs. Engaging with industry partners to advance AI across critical domains leveraging NVIDIA's technology.

Posted 7/28/2026full-timeSanta Clara • California, Texas • 🇺🇸 United StatesSenior💰 $152,000 - $287,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in AI model optimization and performance enhancement on GPU architectures, with strong proficiency in C++ programming and ML/DL frameworks. Capable of collaborating effectively with cross-functional teams to drive innovation in AI technologies.

Highest-signal resume keywords

C++ ProgrammingAI Inferencing PipelinesML/DL FrameworksPerformance OptimizationData Structures and Algorithms

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

C++ ProgrammingData StructuresAlgorithmsAI Model OptimizationQuantizationDistillationPruningEnd-to-End OptimizationInference Runtime FeaturesMultitasking

Soft Skills

Analytical AbilitiesProblem-SolvingWritten CommunicationOral CommunicationCollaboration

Tools & Technologies

ONNX RTPyTorchTensor RTLlama.cppVLLM

Industry Keywords

AI EcosystemGPU ArchitecturesEdge DevicesOpen Source TechnologiesClosed Source Technologies

Tech Stack

Tools & technologies

C++PyTorch

About the role

Key responsibilities & impact

Partnering with NVIDIA software, research, architecture, and product teams to align strategies and technical needs for fostering the ecosystem of AI on RTX and DGX PCs.
Collaborate closely with industry partners to advance AI across critical domains—including graphics, web browsers, and edge devices—by driving innovation in both open and closed source technologies with emphasis on system level support.
Improving performance on current and next-generation GPU architectures by conducting in-depth analysis and end-to-end optimization of AI models, data processing pipelines, and inference runtime features.
Identifying, evaluating, and implementing compute and memory optimization techniques—such as quantization, distillation, and pruning—for large AI models; fine-tuning and compressing models to fit edge devices.

Requirements

What you’ll need

Bachelor's, Master's, or PhD in Computer Science, Software Engineering, Mathematics, or a related field (or equivalent experience).
Excellent C++ programming and debugging skills with a strong understanding of data structures and algorithms.
5+ years of experience with proficiency in AI inferencing pipelines and applications using ML/DL frameworks, including ONNX RT, PyTorch, Tensor RT, llama.cpp and vLLM.
Strong analytical and problem-solving abilities, with the ability to multitask effectively in a dynamic environment.
Outstanding written and oral communication skills enabling effective collaboration with management and engineering teams.

Benefits

Comp & perks

equity
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