NVIDIA

2 days ago

Senior Performance Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 day agoStatus: Live

Job Summary

Build and evolve performance analysis and telemetry systems for large-scale GPU and CPU clusters used in AI and high-performance computing. Profile and benchmark AI/HPC workloads, investigate networking and collective communication performance (NCCL, RDMA, MPI, RoCE), and identify bottlenecks across compute, memory, and system architecture. Develop diagnostic and benchmarking tools, define test plans, and collaborate across hardware, firmware, networking, systems, and software teams.

Location: Israel

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Profile, benchmark, and analyze AI and HPC workloads on GPU and CPU clusters.
•Explore performance characteristics of high-performance networking and collective communications (NCCL, RDMA, MPI, RoCE).
•Identify performance bottlenecks across networking, compute, memory, and system architecture.
•Develop and enhance performance analysis, benchmarking, and diagnostic tools.
•Collaborate across hardware, firmware, networking, systems, and software teams to deliver actionable performance insights.

Key Requirements

•B.Sc. or M.Sc. in Computer Science, Computer Engineering, Software Engineering, or equivalent experience.
•5+ years of experience in performance analysis, systems engineering, or HPC/AI infrastructure.
•Demonstrated expertise in performance analysis skills and methodologies.
•Hands-on experience with high-performance networking (RDMA, MPI, NCCL, congestion control).
•Strong understanding of system performance metrics (latency, throughput, resource utilization).

Experience:5+ yearsHPCAI infrastructure

Education:Bachelor's in Computer Science, Computer Engineering, Software Engineering

Skills:Analytical thinkingProblem-solvingCommunicationCross-functional collaboration

Tech Stack:NCCLRDMAMPIRoCECUDAPythonBashCC++LinuxPyTorchTensorFlowPCIeNVIDIA GPUs

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: 4.3

Website LinkedIn Glassdoor

Loading job details...

Preparing the role view and application actions.

NVIDIA

2 days ago

Senior Performance Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 day agoStatus: Live

Job Summary

Location: Israel

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Profile, benchmark, and analyze AI and HPC workloads on GPU and CPU clusters.
•Explore performance characteristics of high-performance networking and collective communications (NCCL, RDMA, MPI, RoCE).
•Identify performance bottlenecks across networking, compute, memory, and system architecture.
•Develop and enhance performance analysis, benchmarking, and diagnostic tools.
•Collaborate across hardware, firmware, networking, systems, and software teams to deliver actionable performance insights.

Key Requirements

•B.Sc. or M.Sc. in Computer Science, Computer Engineering, Software Engineering, or equivalent experience.
•5+ years of experience in performance analysis, systems engineering, or HPC/AI infrastructure.
•Demonstrated expertise in performance analysis skills and methodologies.
•Hands-on experience with high-performance networking (RDMA, MPI, NCCL, congestion control).
•Strong understanding of system performance metrics (latency, throughput, resource utilization).

Experience:5+ yearsHPCAI infrastructure

Education:Bachelor's in Computer Science, Computer Engineering, Software Engineering

Skills:Analytical thinkingProblem-solvingCommunicationCross-functional collaboration

Tech Stack:NCCLRDMAMPIRoCECUDAPythonBashCC++LinuxPyTorchTensorFlowPCIeNVIDIA GPUs

Company Brief

NVIDIA

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: 4.3

Website LinkedIn Glassdoor