Senior GPU Memory Architect

🕒 February 27

🏄 California, North Carolina, +2 more states – Remote

🏄 California – Remote 🌲 North Carolina – Remote 🤠 Texas – Remote ☕ Washington – Remote

💵 $184k - $356.5k / year

⏰ Full Time

🟠 Senior

🏛️ Architect

🦅 H1B Visa Sponsor

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👻 Ghost score 46%

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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

• Develop innovative high-performance processor and system architectures focused on memory systems and energy efficiency • Develop and enhance architecture and micro-architecture features for GPU memory systems, optimizing performance per watt, performance per millimeter, and performance per dollar • Develop and enhance architecture prototype models for power and noise analysis • Participate in performance and power simulation of features to analyze, define, and improve energy per byte • Analyze benchmarks, application workloads, and performance/power simulation and emulation results to identify architecture optimization opportunities • Debug power, performance, and functional issues using high-level models, RTL simulation and emulation, silicon, and systems • Collaborate with outside partners on system infrastructure

🎯 Requirements

• 10+ yrs of experience in CPU/GPU architecture and memory systems design with a focus on energy efficiency in the system • Bachelor's degree in Electrical Engineering, Computer Science, or related field, or equivalent experience • Expertise in power analysis and modeling in pipeline-based architectures • Good understanding of power analysis tools such as Ansys Power Artist and Synopsys PTPX • Experience with C, C++, and scripting languages • MS/PhD in Electrical Engineering, Computer Science, or related field • Experience with hardware design languages such as Verilog or VHDL • Prior experience developing and optimizing algorithms for power efficiency • Demonstrated ability to innovate and drive continuous improvement in system architecture • Excellent written and verbal communication skills for collaboration with internal teams and external partners

🏖️ Benefits

• Equity • Benefits