Senior Systems Software Engineer - GPU Performance at Scale

NVIDIA
Santa Clara
Workplace: OnsiteFull timeUSD 184,000 - 356,500 annuallyFunction: Solutions Engineering & Sales EngineeringExperience: 8+ yearsEducation: bachelorsSkills: ["Communication","Teamwork","Analytical"]

Lead performance initiatives for at-scale AI datacenter systems, building tools and workflows to validate and optimize GPU-accelerated workloads. Collaborate with HW/FW/SW teams to optimize AI pipelines using CUDA/PyTorch, across large-scale infrastructure, HPC environments, and cloud/container platforms.

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FursaFursa
NVIDIA
NVIDIA
6 months ago

Senior Systems Software Engineer - GPU Performance at Scale

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 22 hours agoStatus: Live

Job Summary

Lead performance initiatives for at-scale AI datacenter systems, building tools and workflows to validate and optimize GPU-accelerated workloads. Collaborate with HW/FW/SW teams to optimize AI pipelines using CUDA/PyTorch, across large-scale infrastructure, HPC environments, and cloud/container platforms.
Location: Santa Clara
Workplace: Onsite
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Manager level

Key Responsibilities

  • •Lead all aspects of implementing performance practices in large scale infrastructure, deliver powerful tools, methodologies, and flows to validate and improve several datacenter products in parallel.
  • •Align the next generation AI workloads on top of next generation datacenter designs, engaging HW/FW/SW/platform internal and customer teams.
  • •Deliver engineering solutions to provide continuous insights into performance of AI workloads over evolving environments, identifying improvements and regressions.
  • •Decompose high-complexity performance or stability issues into minimal reproduction cases and drive to root cause.
  • •Collaborate with SW and FW teams to develop best-in-class practices and tools for AI workload performance at scale.

Pay and Benefits

Salary: USD 184,000 - 356,500 annually
Equity and Bonus:Equity
Perks:Equity

Key Requirements

  • •8+ years of experience in using accelerated computing for datacenter container computing solutions.
  • •Proven understanding of accelerated computing software stacks and DL Frameworks (CUDA, PyTorch).
  • •Experience using and handling modern Cloud and container-based Enterprise computing architectures.
  • •C/C++/Python/Bash programming/scripting experience.
  • •BS in Engineering, Mathematics, Physics, or Computer Science; MS or PhD desirable (or equivalent experience).
Experience:8+ yearsAccelerated computingDatacenterHPCGPUAI
Education:Bachelor's
Skills:CommunicationTeamworkAnalytical
Tech Stack:CUDAPyTorchC++PythonBashLinuxDockerKubernetes

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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