Senior Deep Learning Software Infrastructure Engineer
NVIDIA· Engineer, Sys SW
Hybrid (US, CA)$224k - $356.5kFull-timePosted 2mo ago
About the role
Senior role focused on building and scaling training libraries and infrastructure for autonomous driving applications, enabling multi-thousand GPU training, massive datasets, and efficient end-to-end training pipelines in collaboration with research and platform teams.
Responsibilities
- Crafting, scaling, and hardening deep learning infrastructure libraries and frameworks for training on multi-thousand GPU clusters.
- Improving efficiency throughout the training stack: data loaders, distributed training, scheduling, and performance monitoring.
- Building robust training pipelines and libraries to handle massive video datasets and enable rapid experimentation.
- Collaborating with researchers, model engineers, and internal platform teams to enhance efficiency, minimize stalls, and improve training availability.
- Owning core infrastructure components such as orchestration libraries, distributed training frameworks, and fault-resilient training systems.
- Partnering with leadership to ensure infrastructure scales with growing GPU capacity and dataset size while maintaining developer efficiency and stability.
Qualifications
- BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, or a related field, or equivalent experience.
- 12+ years of professional experience building and scaling high-performance distributed systems, ideally in ML, HPC, or large-scale data infrastructure.
- Extensive knowledge in deep learning frameworks (PyTorch preferred), large scale training (DDP/FSDP, NCCL, tensor/pipeline parallelism), and performance profiling.
- Strong systems background: datacenter networking (RoCE, IB), parallel filesystems (Lustre), storage systems, schedulers (Slurm, Kubernetes, etc.).
- Proficiency in Python with experience writing production-grade libraries, orchestration layers, and automation tools.
- Ability to work closely with multi-functional teams (ML researchers, infra engineers, product leads) and translate requirements into robust systems.
Skills
Required:PyTorchDistributed trainingSystems programmingPython
Benefits
- equity
- benefits (see NVIDIA benefits page)
Last updated Sep 11, 2026. Interested? Apply on the company site.
About NVIDIA
World Leader in AI Computing
NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.
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