NVIDIA
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DGX Cloud Performance Engineer
role at
NVIDIA .
We are seeking highly skilled Parallel and Distributed Systems engineers to drive the performance analysis, optimization, and modeling to define the architecture and design of Nvidia’s DGX Cloud clusters.
Seniority level: Mid‑Senior level.
Employment type: Full-time.
Job function: Computer Hardware Manufacturing, Software Development, and Computers and Electronics Manufacturing.
What You Will Be Doing
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.
What We Need To See
Expertise in working with large scale parallel and distributed accelerator-based system 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 as well as an 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, …).
Ways To Stand Out From The Crowd
PhD in the relevant areas.
Very high intellectual curiosity; confidence to dig in as needed; not afraid of confronting complexity; able to pick up new areas quickly.
Proficiency in CUDA, XLA.
Excellent interpersonal skills.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, autonomous and love a challenge, we want to hear from you.
Compensation: Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is $184,000 – $287,500 for Level 4, and $224,000 – $356,500 for Level 5. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 25, 2025.
EEO Statement NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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DGX Cloud Performance Engineer
role at
NVIDIA .
We are seeking highly skilled Parallel and Distributed Systems engineers to drive the performance analysis, optimization, and modeling to define the architecture and design of Nvidia’s DGX Cloud clusters.
Seniority level: Mid‑Senior level.
Employment type: Full-time.
Job function: Computer Hardware Manufacturing, Software Development, and Computers and Electronics Manufacturing.
What You Will Be Doing
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.
What We Need To See
Expertise in working with large scale parallel and distributed accelerator-based system 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 as well as an 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, …).
Ways To Stand Out From The Crowd
PhD in the relevant areas.
Very high intellectual curiosity; confidence to dig in as needed; not afraid of confronting complexity; able to pick up new areas quickly.
Proficiency in CUDA, XLA.
Excellent interpersonal skills.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, autonomous and love a challenge, we want to hear from you.
Compensation: Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is $184,000 – $287,500 for Level 4, and $224,000 – $356,500 for Level 5. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 25, 2025.
EEO Statement NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
#J-18808-Ljbffr