Software QA & Automation Engineer

NeuReality's software department is looking for an experienced and highly motivated Software QA & Automation Engineer to join us and be part of NeuReality’s next generation state-of-the-art AI inference server development.

The group designs, develops, validates, and releases inference server and programming SDK software products to make AI deployment easy and cost/power[1]effective.

Responsibilities:

The Software QA & Automation Engineer is responsible for all aspects of software testing and release:

• QA activities that are required for releasing high quality products to NeuReality's customers.

• Tight collaboration with architects and development teams

• Reviewing specifications and technical design documents to provide timely and meaningful feedback.

• Creating product test plans and managing their execution

• Defining metrics for quality evaluation

• Design and development of new automatic testing approaches for various features and products developed by NeuReality.

• Consistently reviewing, analyzing, and improving test automation infrastructure and reports

• BSc in Computer Engineering/Computer Science/Electrical Engineering
• 5+ years’ experience in developing automation/validation products (Python, Java or Javascript).
• Experience in validation of complex systems and performance tests
• Formal and practical knowledge of testing methodologies
• Hands-on expertise in test writing and automation
• Excellent knowledge of linux operating system
• Proficiency in test automation tools and frameworks (e.g., Selenium, PyTest, TestNG, JUnit).
• Familiarity with version control systems (e.g., Git) and CI/CD pipelines (e.g., Jenkins, GitLab, or CircleCI).

Problem-Solving and Analytical Skills

• Ability to identify, analyze, and debug issues within complex systems, including AI pipelines.
• Knowledge of data validation and techniques to test AI fairness, bias, and performance.

Communication and Teamwork

• Strong verbal and written communication skills for collaborating with technical and non-technical stakeholders.

Advantages:

AI/ML Knowledge

• Basic understanding of AI/ML concepts, such as training, inference, data preprocessing, and model evaluation.
• Experience testing AI models and ensuring their reliability under diverse data inputs is a plus.
• Computer vision, image, or audio processing knowledge
• Experience working in AI company.
• Experience with testing Cloud/data center applications