Senior DL Systems Engineer, LLM & GPU Performance

NVIDIA Gruppe; Santa Clara (CA); On-site; USD 272,000 - 431,250; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a senior AI systems architect to advance agentic LLM workloads with scalable, datacenter-level design and performance tuning.

You will drive research integration, optimize latency and throughput, and collaborate across internal teams and external partners to define workload requirements. Expertise in deep learning systems, Python, C++, and GPU architectures is essential.

Qualifications

• BS, MS or PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related field (or equivalent).
• 15+ years of experience in deep learning and deep learning systems design.
• Proficiency in Python and C++ programming.
• Strong understanding of computer architecture, and GPU/parallel datacenter computing fundamentals.

Responsibilities

• Research and Development: Explore and incorporate contemporary research on generative AI, agents, and inference systems into the NVIDIA LLM software stack.
• Workload Analysis and Optimization: Profile and optimize agentic LLM workloads to reduce latency and increase throughput while maintaining fidelity.
• System Design and Implementation: Design and implement scalable systems to accelerate agentic workloads for datacenter-scale use cases.
• Collaboration and Communication: Advise on software/hardware/system iterations by engaging with NVIDIA teams and external partners and formalizing workload requirements.

Skills

Python

C++

Deep learning

Performance modeling

Education

BS/MS/PhD in CS/EE/CE or related field

Tools

CUDA

OpenCL

Job description

NVIDIA is seeking a senior AI systems architect to advance agentic LLM workloads with scalable, datacenter-level design and performance tuning.

You will drive research integration, optimize latency and throughput, and collaborate across internal teams and external partners to define workload requirements. Expertise in deep learning systems, Python, C++, and GPU architectures is essential.