
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.
🕒 June 4
🏄 California, Washington – Remote
💵 $184k - $356.5k / year
⏰ Full Time
🟠 Senior
🏛️ Architect
🦅 H1B Visa Sponsor
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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.
• Develop innovative architectures to extend the state of the art in deep learning performance and efficiency • Analyze performance, cost and power trade-offs by developing analytical models, simulators and test suites • Understand and analyze the interplay of hardware and software architectures on future algorithms, programming models and applications • Evaluate PPA (performance, power, area) for hardware features and system level architectural trade-offs. • Develop high level simulators in C++/Python • Actively collaborate with software, product and research teams to guide the direction of deep learning HW and SW
• MS or PhD in Computer Science, Computer Engineering, Electrical Engineering or equivalent experience • 6+ years of relevant meaningful work experience • Strong background in GPU or Deep Learning ASIC architecture for distributed training and/or inference spanning multi-chip/multi-node • Experience with performance modeling, architecture simulation, profiling, and analysis • Solid foundation in machine learning and deep learning. Understanding of modern transformer-based architectures and their performance at scale. • Strong programming skills in Python, C, C++
• equity • benefits
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