Senior Performance Engineer - LLM Inference Frameworks

NVIDIA is hiring a Senior Performance Engineer - LLM Inference Frameworks. Level rates it ; you can apply on NVIDIA.

Level's read on this job

Builds AI ●●●● is how Level rates this role: the job is building AI systems.
Tools and skills the posting cites include Hugging Face, vLLM and PyTorch.
Level classifies it as a senior role.
Level lists 2,700+ other open roles at NVIDIA.

AI in this role

Design, implement, and optimize high-performance LLM inference pipelines and infrastructure on NVIDIA GPUs.

Hugging FacevLLMPyTorchPythonHugging FaceTensorrt LLMSglangNsight Systems

llm-inferenceperformance-engineeringgpu-optimizationquantizationdistributed-systems

NVIDIA is hiring exceptional software engineers to build and optimize the core inference infrastructure for large language models. Join the TensorRT‑LLM team - the group defining how generative AI performs at global scale on NVIDIA GPUs. We’re looking for engineers who love squeezing every drop of throughput, memory efficiency, and scalability out of modern model runtimes. Your work will directly shape the frameworks behind state‑of‑the‑art LLM inference used across NVIDIA and the AI community. Join us to redefine what “fast” means for LLM inference - building the frameworks that power the next generation of generative AI at scale.

What you'll be doing:

Design, implement, and optimize high‑performance inference pipelines for large language models running on GPUs
Profile and tune model execution across the stack - from scheduler design to kernel fusions and everything in-between
Design and experiment with memory management strategies for improved memory bandwidth optimization and cache efficiency
Innovate and Implement cutting-edge techniques such as Speculative Decoding, Context Caching, and FP8/INT4 quantization to push the boundaries of tokens-per-second-per-watt
Develop and maintain benchmarking and testing systems that quantify latency, utilization, and efficiency

What we need to see:

Bachelor's, Master's, or higher degree in Computer Engineering, Computer Science, Applied Mathematics, or related computing-focused degree (or equivalent experience)
5+ years of relevant software development experience.
Excellent Python programming skills, software design, and software engineering skills
Experience working with deep learning frameworks like PyTorch and HuggingFace
Experience profiling and debugging performance at all levels - Python runtime, PyTorch internals, and GPU utilization metrics
Awareness of the latest developments in LLM architectures and LLM inference techniques
Proactive and able to work without supervision
Excellent written and oral communication skills in English

Ways to stand out from the crowd:

Contributions to inference frameworks such as TensorRT‑LLM, vLLM, SGLang, or similar systems
Demonstrated expertise in performance modeling, memory optimization, distributed model execution or GPU execution workflows
Hands‑on experience with NVIDIA profiling tools (Nsight Systems, PyTorch Profiler, custom benchmarking harnesses)
Strong grasp of the trade‑offs shaping inference efficiency: compute vs. memory, scheduling vs. batching, latency vs. throughput

Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com.

#LI-Hybrid

How we rate this

Senior Performance Engineer - LLM Inference Frameworks at NVIDIA rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Performance Engineer - LLM Inference Frameworks is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Israel, Yokneam.
The job was posted on April 20, 2026.
Seniority: senior.
Applications are handled by NVIDIA. Apply on NVIDIA

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

LLM InferencePerformance EngineeringGPU OptimizationQuantizationDistributed SystemsHugging FacevLLMPyTorch

Questions you could be asked

Tell me about a project where llm inference was part of your work. What did you do?
Tell me about a project where performance engineering was part of your work. What did you do?
Tell me about a project where gpu optimization was part of your work. What did you do?
Tell me about a project where quantization was part of your work. What did you do?
Tell me about a project where distributed systems was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: LLM Inference, Performance Engineering, GPU Optimization, Quantization, and Distributed Systems. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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