Join NVIDIA as a Deep Learning Engineer to enhance AI stacks by integrating advanced communication technologies like PyTorch, TRT-LLM, vLLM, SGLang, JAX, and more. You will work closely with the team behind NCCL, NVSHMEM, and GPUDirect to optimize multi-GPU communications for diverse demands from training on up to 100K GPUs to microsecond latency inference. Your daily tasks include analyzing AI workloads, improving compilers, designing fault-tolerant solutions, and authoring custom kernels. Ideal candidates have a B.S., M.S., or Ph.D. in Computer Science with extensive experience in HPC/AI, proficiency in Python, C++, CUDA, and familiarity with performance profiling tools like PyTorch profiler and NVIDIA Nsight Systems.
Skills
PyTorch
C++
CUDA
Python
NCCL
NVSHMEM
JAX
TRT-LLM
vLLM
SGLang
HPC
AI
MPI
TensorRT
NVIDIA_Nsight_Systems
Performance_Profiling
Parallel_Programming
Compiler_Technologies
Memory_Hierarchy
Tensor_Layout
Distributed_Inference
Mixture_of_Experts
Reinforcement_Learning
What you'll do
Integrate new features in AI frameworks like PyTorch and TRT-LLM.
Analyze multi-GPU communication requirements for AI workloads.
Improve AI compilers to optimize communication performance.
Design fault-tolerant solutions for large-scale AI workloads.
Author custom kernels to demonstrate ultimate performance on NV platforms.
What we're looking for
B.S., M.S., or Ph.D. in Computer Science or related field with 5+ years of software engineering experience in HPC/AI.
Development/integration experience with Deep Learning Frameworks like PyTorch, JAX, TRT-LLM, vLLM, and SGLang.
Proficiency in Python, C++, CUDA, Triton, cuTe for rapid prototyping and development.
Solid understanding of AI models, parallelisms, compiler technologies, and performance benchmarking tools.
Experience with HPC/AI communication concepts including 1-sided/2-sided communication, elasticity, resiliency, and topology discovery.
Expertise in training, distributed inference, MoE, reinforcement learning, or kernel authoring on CUDA, Triton, cuTe.
Market check
Salary context
This
$152,000–$241,500
range sits above
40%
of similar postings on FindRole.
Peer median band
$163,450–$257,300
Median floor and ceiling across peers.
Typical midpoint (25–75%)
$180,025–$246,150
Middle half of comparable postings.
Based on 240 comparable postings.*
* 240 is the maximum number of comparable postings sampled.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
801 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 797 roles with salary data.