Senior Deep Learning Sofware Infrastructure Engineer

NVIDIA
California
Workplace: RemoteFull timeUSD 224,000 - 431,250 annuallyFunction: DevOps, Cloud & InfrastructureExperience: 12+ yearsSkills: ["Cross-functional collaboration","Technical ownership","Leadership"]

Build and scale deep learning infrastructure libraries and frameworks that enable end-to-end autonomous driving training on multi-thousand GPU clusters. Improve efficiency across the training stack (data loaders, distributed training, scheduling, performance monitoring), and create robust training pipelines for massive video datasets. Partner with research, model, and internal platform teams to minimize stalls and increase training availability, while owning orchestration, distributed training, and fault-resilient systems.

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FursaFursa
NVIDIA
NVIDIA
2 days ago

Senior Deep Learning Sofware Infrastructure Engineer

✓ Verified Job

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Source: Company careers pageValidated by: Fursa AI
Last checked: 23 hours agoStatus: Live

Job Summary

Build and scale deep learning infrastructure libraries and frameworks that enable end-to-end autonomous driving training on multi-thousand GPU clusters. Improve efficiency across the training stack (data loaders, distributed training, scheduling, performance monitoring), and create robust training pipelines for massive video datasets. Partner with research, model, and internal platform teams to minimize stalls and increase training availability, while owning orchestration, distributed training, and fault-resilient systems.
Location: California
Workplace: Remote
Employment Type: Full time
Job Function: DevOps, Cloud & Infrastructure
Seniority: Mid level

Key Responsibilities

  • •Craft, scale, and harden deep learning infrastructure libraries and frameworks for training on multi-thousand GPU clusters.
  • •Improve efficiency across the training stack, including data loaders, distributed training, scheduling, and performance monitoring.
  • •Build training pipelines and libraries for massive video datasets to enable rapid experimentation.
  • •Collaborate with researchers, model engineers, and internal platform teams to enhance efficiency, minimize stalls, and improve training availability.
  • •Own core infrastructure components such as orchestration libraries, distributed training frameworks, and fault-resilient training systems.

Pay and Benefits

Salary: USD 224,000 - 431,250 annually
Equity and Bonus:Equity

Key Requirements

  • •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) and large-scale training (DDP/FSDP, NCCL, tensor/pipeline parallelism).
  • •Strong systems background including datacenter networking (RoCE, IB), parallel filesystems (Lustre), storage systems, and schedulers (Slurm, Kubernetes, etc.).
  • •Proficiency in Python with experience writing production-grade libraries, orchestration layers, and automation tools.
Experience:12+ yearsMLHPCLarge-scale data infrastructure
Education:
Skills:Cross-functional collaborationTechnical ownershipLeadership
Tech Stack:PythonPyTorchDDPFSDPNCCLTensor parallelismPipeline parallelismRoCEInfiniBand (IB)LustreSlurmKubernetesDistributed trainingPerformance profiling

Company Brief

NVIDIA
Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1993
Glassdoor
Glassdoor: 4.3
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