Senior DL Algorithms Engineer - Inference Performance

NVIDIA•Us, CA

About The Position

We are looking for a Senior DL Algorithms Engineer for LLM/Omni model optimizations! Seeking senior engineers who are mindful of performance analysis and optimization to help us squeeze every last clock cycle out of Deep Learning workloads. If you are unafraid to work across all layers of the hardware/software stack from GPU architecture to Deep Learning Framework to achieve peak performance, we want to hear from you! This role offers an opportunity to directly impact the hardware and software roadmap in a fast-growing technology company that leads the AI revolution.

Requirements

PhD in CS, EE or CSEE or equivalent experience.
3+ years of experience.
Strong background in deep learning and neural networks, in particular inference.
Experience with performance profiling, analysis and optimization, especially for GPU-based applications.
Proficient in PyTorch or equivalent frameworks for AI, or HPC-heavy application development.
Deep understanding of computer architecture, and familiarity with the fundamentals of GPU architecture.

Nice To Haves

Proven experience with processor and system-level performance optimization.
Deep understanding of modern LLM/Diffusion architectures.
Strong fundamentals in algorithms.
GPU programming experience (CUDA or OpenCL) is a strong plus.

Responsibilities

Enable and optimize state-of-the-art open models (like Nemotron and Cosmos) on NVIDIA’s accelerated inference SW stack.
Contribute new features, fix bugs and deliver production code to open-source frameworks like TRT-LLM, vLLM, SGLang, FlashInfer, etc.
Profile and analyze bottlenecks across the full inference stack to push the boundaries of inference performance.
Benchmark state-of-the-art offerings and perform competitive analysis for NVIDIA’s SW/HW stack.
Co-design with partner teams to develop the next generation of AI models and services.