Software Engineer, DGX Cloud AI Infrastructure

What you’ll be doing:

• 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.

What we need to see:

• 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.
• Backgroun 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.

Ways to stand out from the crowd:

• Hands-on experience with NCCL and CUDA-aware distributed execution.
• Deep familiarity with the RDMA software stack (NCCL, IB verbs, UCX, libfabric) and with InfiniBand / RoCE congestion debugging.
• Experience building acceptance tests, benchmark harnesses, regression gates, or cluster qualification tooling for AI platforms, including MLPerf.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

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.

Originally posted on Himalayas