Senior Deep Learning Systems Architect

NVIDIA
Santa Clara
Workplace: OnsiteFull timeUSD 224,000 - 356,500 annuallyFunction: Software EngineeringExperience: 10+ yearsSkills: ["Collaboration","Problem-solving","Analytical thinking","Benchmarking"]

Design next-generation hardware accelerator and processor architectures that enable state-of-the-art machine learning and data analytics on NVIDIA’s mobile, embedded, and datacenter platforms. Join the deep learning architecture team to co-design AI systems from conception through prototyping, translate AI/DL workloads into underlying hardware and system optimizations, and improve performance by identifying bottlenecks. Collaborate across DL research, hardware architecture, and software engineering using first-principles analysis and benchmarking.

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FursaFursa
NVIDIA
NVIDIA
1 month ago

Senior Deep Learning Systems Architect

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Source: Company careers pageValidated by: Fursa AI
Last checked: 8 hours agoStatus: Live

Job Summary

Design next-generation hardware accelerator and processor architectures that enable state-of-the-art machine learning and data analytics on NVIDIA’s mobile, embedded, and datacenter platforms. Join the deep learning architecture team to co-design AI systems from conception through prototyping, translate AI/DL workloads into underlying hardware and system optimizations, and improve performance by identifying bottlenecks. Collaborate across DL research, hardware architecture, and software engineering using first-principles analysis and benchmarking.
Location: Santa Clara
Workplace: Onsite
Employment Type: Full time
Job Function: Software Engineering
Seniority: Mid level

Key Responsibilities

  • •Contribute to deep learning architecture features that advance next-generation GPUs and AI systems.
  • •Stay current on deep learning research and collaborate with DL researchers, hardware architects, and software engineers.
  • •Co-design AI system architectures from conception, specification, and prototyping for NVIDIA offerings.
  • •Map AI/DL workloads to underlying hardware and systems, identifying bottlenecks and proposing performance improvements.
  • •Perform first-principles analyses of deep learning techniques, build analytical models, implement prototypes, and benchmark results.

Pay and Benefits

Salary: USD 224,000 - 356,500 annually
Equity and Bonus:Equity

Key Requirements

  • •MS (or equivalent) or PhD in computer science, computer architecture, electrical engineering, or related field, with 10+ years of relevant work experience.
  • •Strong foundation in deep neural networks and deep learning fundamentals, including adapting/training DNNs for various tasks.
  • •Experience developing code for DNN training frameworks such as PyTorch, TensorFlow, or JAX.
  • •Programming fluency with C++ and ideally Python.
  • •Work experience with GPU computing (CUDA, OpenCL, OpenACC) and HPC (MPI, OpenMP) is a plus.
Experience:10+ years
Education:
Skills:CollaborationProblem-solvingAnalytical thinkingBenchmarking
Tech Stack:C++PythonPyTorchTensorFlowJAXCUDAOpenCLOpenACCMPIOpenMP

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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