Senior Software Engineer, DGX Cloud AI Infrastructure

Nvidia

Confirmed live today High trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CAAustin, TXORWARedmond, WA
Salary: $184,000–$287,500 / yr
Employment: Full-time
Posted: 28 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $194k

This role $236k

$136k $304k

below market most similar roles pay here above market

This role pays more than 81% of similar roles. Most pay $152,591–$235,750 — the blue band above. At the midpoint, this role pays about $236k versus about $194k for comparable roles.

Based on 240 similar postings.

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 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Senior Software Engineer, DGX Cloud AI Infrastructure

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The Senior Software Engineer, DGX Cloud AI Infrastructure joins the team to lead the bring-up, benchmarking, and optimization of distributed training and inference workloads across large-scale GPU platforms. You will perform deep performance investigations on multi-GPU and multi-node deployments, setting technical direction for communication libraries and model frameworks. Daily responsibilities include profiling end-to-end workload performance, owning root-cause analysis for complex failures, and building resilience and failure-attribution capabilities. You will utilize PyTorch, NeMo, Megatron, TensorRT-LLM, NCCL, and Nsight Systems to optimize data, tensor, and pipeline parallelism. The role requires expert-level Python and C/C++ skills to solve technical problems involving GPU cluster fabrics, RDMA software stacks, and large-scale distributed systems to ensure state-of-the-art large language model workloads run efficiently and reliably.

What does a Software Engineer earn in California?

Median $214500 from 1193 postings across 76 companies.

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Skills

Python C/C++ PyTorch TensorRT-LLM NeMo Megatron CUDA NCCL RDMA InfiniBand RoCE NVLink NVSwitch Nsight Systems Distributed Computing HPC Deep Learning Systems

What you'll do

Lead the bring-up, validation, and debugging of large-scale AI clusters and end-to-end workloads.
Tune and benchmark AI pre-training and inference workloads using PyTorch, NeMo, and TensorRT-LLM.
Profile and optimize performance across compute, memory, networking, and communication layers using Nsight Systems and NCCL.
Analyze scaling efficiency for distributed LLM workloads using data, tensor, pipeline, and expert parallelism.
Perform root-cause analysis on complex failures, hangs, and performance regressions in large distributed environments.
Build resilience and failure-attribution stacks to detect and triage node, fabric, and workload failures.
Create repeatable benchmark suites, automation, and qualification workflows for new hardware platforms.
Provide data-driven tuning guidance for runtime settings, communication parameters, and deployment configurations.

What we're looking for

Bachelor’s or Master’s in Computer Science or a related technical field, or equivalent experience.
8+ years of experience developing software infrastructure for large-scale AI or HPC systems.
Expertise debugging and triaging AI applications across the full stack from the application layer down to the hardware.
Deep hands-on experience with NCCL, CUDA-aware distributed execution, and debugging multi-GPU and multi-node workloads at scale.
Proven track record of architecting, debugging, and scaling large-scale distributed systems.
Expert-level Python and C/C++ programming skills.
Experience operating workloads in scheduled, containerized cluster environments.
Deep familiarity with the RDMA software stack (NCCL, IB verbs, UCX, libfabric) (preferred).

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