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About the Role

NVIDIA is at the forefront of the generative AI revolution, building the software and systems that power the world’s most advanced large language model workloads. This role focuses on bring-up, triage, benchmarking, analysis, and optimization of distributed training and inference workloads across NVIDIA GPU platforms at the largest scales. You will help bring up, benchmark, and debug distributed LLM workloads on multi-GPU and multi-node deployments, and own the design and implementation of benchmarking tooling, automation, and debugging workflows.

Responsibilities

Bring up, validate, and debug large-scale AI clusters, infrastructure, and end-to-end workloads.
Bring up, tune, and benchmark AI pre-training, post-training, and inference workloads using PyTorch, NeMo / Megatron, TensorRT-LLM, and adjacent NVIDIA AI software stacks.
Perform root-cause analysis of failures in large distributed environments.
Contribute to the resilience and failure-attribution tooling that detects, triages, and attributes node, fabric, and workload failures across the cluster.
Build and maintain repeatable benchmark suites, automation, acceptance criteria, and qualification workflows on new platforms.
Tune runtime settings, communication parameters, and deployment configurations in close partnership with framework, systems, and platform teams.
Deliver actionable, data-driven recommendations based on profiling, benchmark results, and cluster characterization.

Requirements

Bachelor’s or Master’s in Computer Science or a related technical field (or equivalent experience).
3+ years of experience developing software for AI, HPC, or systems-level applications.
Hands-on experience with multi-GPU or multi-node workloads and CUDA-aware distributed execution.
Background with debugging and scaling distributed systems.
Experience debugging and triaging AI applications across the full stack, from the application level toward the hardware.
Experience operating workloads in scheduled, containerized cluster environments.
Excellent analytical, debugging, and communication skills, and a collaborative approach across teams.
Strong Python and C/C++ programming skills.

Skills

NCCL
CUDA-aware distributed execution
RDMA software stack (NCCL, IB verbs, UCX, libfabric)
InfiniBand / RoCE congestion debugging
Acceptance tests
Benchmark harnesses
Regression gates
Cluster qualification tooling for AI platforms
MLPerf
Performance jitter diagnosis
Resilience systems
Fault-detection systems
Failure-attribution systems for datacenter-scale infrastructure

Location

Remote

Work Type

Full-time

Experience Level

3+ years

Education Level

Bachelor's or Master's in Computer Science or related technical field (or equivalent experience)

Salary/Compensations

116,000 USD - 189,750 USD for Level 2
140,000 USD - 224,250 USD for Level 3

Benefits

Equity
Benefits

About the Company

NVIDIA is widely considered to be one of the technology world’s most desirable employers.
We have some of the most forward-thinking and hardworking people in the world working for us.
NVIDIA pioneered accelerated computing.
Today, our AI infrastructure powers global intelligence, transforming every industry.
Learn more about NVIDIA.

Equal Opportunity

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer.
As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.