AI Compute QA Engineer – Hybrid (Test ML Workloads)

Texas Instruments

Atlanta (GA)

Hybrid

USD 90,000 - 150,000

Full time

14 days+

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Job summary

d-Matrix in Santa Clara, CA, is seeking a software QA engineer to qualify and productize our AI compute engine within the Software Qualification team. You will develop test suites, test cases, and test infrastructure, and work closely with software development to design, automate, and execute use cases for the AI chip software stack.

Strong Python programming, Linux experience, and knowledge of CI/CD pipelines (Jenkins, GitLab) are required.

Qualifications

  • Startup experience is preferred.
  • Experience testing and automating ML/AI workloads.
  • Experience with system hardware and software testing.
  • Experience with Linux OS and Linux kernel.
  • Experience with Jira, GitLab, Docker or other CI/CD tools.
  • Excellent cross‑geography teamwork and communication.

Responsibilities

  • Qualify and productize d‑Matrix AI compute engine as part of the Software Qualification team.
  • Develop test suites, test cases, and test infrastructures.
  • Collaborate with software teams to design, automate, and execute use cases for the AI chip software stack.
  • Implement Python programs to test workloads and ML models within the Pytest framework.
  • Improve end‑to‑end and regression test suites in CI/CD using pytest, Jenkins, and GitLab.
  • Coordinate with product, software, and systems teams on test coverage and results.
  • Engage in test case implementation, bug triaging and debugging.
  • Show strong Python programming proficiency.

Skills

Python programming
Testing & automation
Linux
CI/CD
Jira
GitLab
Docker
Communication

Education

Bachelor's in Computer Science or Engineering
Master's in Computer Science or Engineering

Tools

Jira
GitLab
Docker

Job description

d-Matrix in Santa Clara, CA, is seeking a software QA engineer to qualify and productize our AI compute engine within the Software Qualification team. You will develop test suites, test cases, and test infrastructure, and work closely with software development to design, automate, and execute use cases for the AI chip software stack.

Strong Python programming, Linux experience, and knowledge of CI/CD pipelines (Jenkins, GitLab) are required.

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