Senior Deep Learning Performance Architect

🕒 2 days ago

🏄 California, Washington – Remote

🏄 California – Remote ☕ Washington – Remote

💵 $184k - $356.5k / year

⏰ Full Time

🟠 Senior

🏛️ Architect

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

Apply Now

Find Similar Remote Jobs

Receive Emails For Remote Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

Artificial Intelligence • Gaming • Automotive

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 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

🎯 Requirements

• 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++

🏖️ Benefits

• equity • benefits