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NVIDIA

Designs the chips and software that power AI

Senior QA Automation Engineer - ASIC Simulation

Test Automation EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • Have 5 or more years of hands-on QA or networking experience, with CCNP-equivalent protocol knowledge in Layer 2 (VLAN and STP), Layer 3 (BGP and OSPF), EVPN, VXLAN, PFC, ECN, RoCE, and QoS.
  • Have production-quality Python engineering experience, including strong object-oriented design and hands-on experience with Pytest.
  • Have deep Linux proficiency equivalent to LPIC-1 or LPIC-2, including navigating system internals, analyzing logs, and debugging.
  • Have clear verbal and written communication skills and professional proficiency in written and spoken English.
  • Have a B.Sc. or B.A. in Computer Science, Electrical Engineering, or a similar background, or equivalent experience.

Responsibilities

  • Review architectural designs and requirements for new product features.
  • Drive the design, development, and execution of functional, performance, and security tests for software general availability and update releases.
  • Develop Python automation suites using object-oriented programming principles.
  • Investigate defects and validate fixes through resolution of the root cause.
  • Use the SimX platform to validate code and debug the ASIC before hardware is available.

Desired Qualifications

  • Have experience with Docker and traffic generation tools such as Ixia, TRex, or Scapy.
  • Have hands-on experience integrating tests into continuous integration and continuous delivery pipelines such as Jenkins or GitLab CI.
  • Have working knowledge of virtualization platforms such as KVM or VMware.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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