Cloud Performance Engineer

Job not on LinkedIn

October 22

Apply Now
Logo of NVIDIA

NVIDIA

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.

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

📋 Description

• Develop benchmarks, end to end customer applications running at scale, instrumented for performance measurements, tracking, sampling, to measure and optimize performance of important applications and services; • Construct carefully designed experiments to analyze, study and develop critical insights into performance bottlenecks, dependencies, from an end to end perspective; • Develop ideas on how to improve the end to end system performance and usability by driving changes in the HW or SW (or both). • Collaborate with AI researchers, developers, and application service providers to understand internal developer and external customer pain points, requirements, project future needs and share best practice. • Develop the necessary modeling framework and the TCO (total cost of ownership) analysis to enable efficient exploration and sweep of the architecture and design space • Develop the methodology needed to drive the engineering analysis to Inform the architecture, design and roadmap of DGX Cloud

🎯 Requirements

• Expertise in working with large scale parallel and distributed accelerator-based systems • Expertise optimizing performance and AI workloads on large scale systems • Experience with performance modeling and benchmarking at scale • Strong background in Computer Architecture, Networking, Storage systems, Accelerators • Familiarity with popular AI frameworks (PyTorch, TensorFlow, JAX, Megatron-LM, Tensort-LLM, VLLM) among others • Experience with AI/ML models and workloads, in particular LLMs • understanding of DNNs and their use in emerging AI/ML applications and services • Bachelors/Masters in Engineering or equivalent experience (preferably, Electrical Engineering, Computer Engineering, or Computer Science) • 10 years experience in the above areas • Proficiency in Python, C/C++ • Expertise with at least one of public CSP infrastructure (GCP, AWS, Azure, OCI, …)

🏖️ Benefits

• equity • benefits

Apply Now

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