NVIDIA | vLLM + SGLang | Deep Learning Inference | Remote (North America preferred)

Hi everyone — I’m Akbar, Senior Manager of Deep Learning Inference Software at NVIDIA. I lead our engineering efforts around vLLM and SGLang, two of the most widely used open-source LLM inference frameworks.

We’re building teams focused on making LLM inference faster, more efficient, and more reliable at scale — from runtime and scheduling optimizations to kernel fusion, distributed serving, and continuous integration across new GPU architectures (Hopper, Blackwell, etc.).

We’re hiring for multiple roles:

• Senior Deep Learning Software Engineer, Inference (https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSit...)

• Engineering Manager, Deep Learning Inference (https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSit...)

• DL Performance Software Engineer - LLM Inference (https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCar...)

• DL Performance Software Engineer - LLM Inference (https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCar...)

These roles are remote-friendly (North America preferred) and fully focused on upstream open-source development — working directly with the maintainers and the wider AI community.

If you’re excited about large-scale inference, compiler/runtime performance, and pushing GPUs to their limits, we’d love to talk.

I noticed the DL Performance Engineer positions are not listed as remote. Is this correct?