Senior Software Engineer, AI Performance Analysis

🕒 July 16

🏄 California, Oregon – Remote

🏄 California – Remote 🌲 Oregon – Remote

💵 $184k - $356.5k / year

⏰ Full Time

🟠 Senior

🤖 AI Engineer

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Design and build performance analysis tools and workflows for AI training and inference workloads • Understand AI performance engineers' workflows and translate their needs into scalable, intuitive tooling • Develop integrations between profiling infrastructure and AI frameworks and workflows • Collaborate with performance engineers, hardware architects, and software teams • Identify performance bottlenecks in AI workloads and develop automated approaches to detect and diagnose them

🎯 Requirements

• M.S. or PhD in Computer Science, Computer Engineering, or a related field, or equivalent experience • 6+ years of relevant work experience • Deep knowledge of AI workloads, frameworks, and performance characteristics • Experience building tools, workflows, or infrastructure used by other engineers • Strong software development skills; Python and C++ preferred • Ability to translate user requirements into scalable tooling solutions • Up to date with AI-enabled tooling for software development and performance analysis • Strong interpersonal skills for understanding engineer difficulties and working across multifunctional teams • Experience profiling or optimizing AI training or inference pipelines at scale • Background building developer tools or platforms for ML engineers • Contributions to open-source AI tooling or frameworks

🏖️ Benefits

• Equity • Benefits • Equal opportunity employer