About the role
Requirements:
- Solid foundation in computer science fundamentals (data structures, algorithms, operating systems, and basic computer architecture).
- Hands-on experience designing, automating, or running performance, load, stress, or regression tests for distributed systems.
- Some experience with QA automation in bare-metal or Kubernetes environments (comfort with at least one is expected; exposure to both is a plus).
- Good programming skills in Python, along with working knowledge of Linux scripting.
- Basic understanding of AI models and inference engines, or a strong interest in learning benchmarking/evaluation methodologies for inference workflows.
- Familiarity with modern dev and QA toolchains, including AI-assisted development tools (e. g., VS Code, GitHub, and Copilot).