Manager, GPU Accelerated Data Analytics

NVIDIA
Santa Clara, New York
Workplace: HybridFull timeFunction: Software EngineeringExperience: 7+ yearsEducation: mastersSkills: ["Leadership","Communication","Collaboration","Mentoring","Presentation"]

Lead a distributed team of performance engineers, collaborating with developers to optimize CPU/GPU workloads on NVIDIA’s platform, driving innovation and architectural decisions, and shaping initiatives for performance-first prototypes across cloud and on-prem environments.

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FursaFursa
NVIDIA
NVIDIA
6 months ago

Manager, GPU Accelerated Data Analytics

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Job Summary

Lead a distributed team of performance engineers, collaborating with developers to optimize CPU/GPU workloads on NVIDIA’s platform, driving innovation and architectural decisions, and shaping initiatives for performance-first prototypes across cloud and on-prem environments.
Location: Santa Clara, New York
Workplace: Hybrid
Employment Type: Full time
Job Function: Software Engineering
Seniority: Manager level

Key Responsibilities

  • •Lead a distributed world-class team of performance engineers; grow domain, hardware and software expertise within the team.
  • •Drive technical excellence by leading software design decisions and influencing architecture roadmap.
  • •Collaborate with company leadership, research teams, and cross-functional partners to drive strategic initiatives.
  • •Research, analyze, and develop innovative techniques to optimize performance of complex workloads across cloud and on-prem environments.
  • •Communicate technical solutions effectively to multi-functional teams and advocate for next-generation hardware/software products.

Pay and Benefits

Equity and Bonus:Equity
Perks:Equity

Key Requirements

  • •MS or PhD in Computer Science, Computer Engineering, or related computational science degree (or equivalent experience).
  • •7+ overall years of relevant experience with 4+ years in a technical role and 3+ years in an engineering leadership role.
  • •Hands-on experience in low-level performance optimization, including GPU parallel programming (CUDA).
  • •Programming fluency in C/C++ with deep understanding of algorithms and software development.
  • •In-depth expertise with CPU and GPU architecture fundamentals.
Experience:7+ yearsAccelerated computingGPUCUDACPU architecture
Education:Master's in Computer Science
Skills:LeadershipCommunicationCollaborationMentoringPresentation
Languages:English
Tech Stack:C++CUDAGPUCPU architecture

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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