Inference Service QA Tech Lead

As an Inference Service QA Tech Lead at Cerebras Systems, your main responsibilities include developing thorough test plans and executing various tests such as functional, integration, and regression tests. You'll also lead the QA team, define methodologies, select appropriate tools, and drive automated test development. Additionally, you will implement quality metrics to measure product and process quality, leading bug triage processes, and providing updates on quality to stakeholders.

To qualify for the Inference Service QA Tech Lead role at Cerebras Systems, candidates should have 5+ years of experience building QA systems for cloud-based SaaS or API services, ideally with a focus on AI systems. Proficiency in at least one high-level programming language, experience with test automation, and strong communication skills are essential. Additionally, familiarity with tools such as Jira and experience working with geographically dispersed teams are important.

The Inference Service QA Tech Lead plays a vital role at Cerebras Systems by ensuring the quality and reliability of our AI products. By developing and executing a comprehensive QA strategy, selecting appropriate methodologies, and leading the development of automated tests, this role is essential in maintaining the high standards that Cerebras is known for within the AI industry.

Cerebras Systems offers a unique working environment for the Inference Service QA Tech Lead with its groundbreaking technology and culture. Employees have the chance to work on revolutionary AI systems, enjoy job stability, and be part of a non-corporate work culture that values individual contributions and perspectives. The company supports continuous growth and aims to empower employees to excel in their roles.

The Inference Service QA Tech Lead role at Cerebras Systems follows a hybrid work schedule, requiring in-office presence for three days a week. This setup fosters collaboration amongst teams while allowing some flexibility suitable for balancing work and personal life.

In your response, focus on specific tools and frameworks you have utilized for test automation, mentioning any relevant QA systems you have built for cloud-based services. Discuss the challenges you faced and how you overcame them to improve overall testing efficiency.

When answering this question, highlight the importance of quality metrics in driving continuous improvement. Provide examples of metrics you have defined in past roles, what tools you used to track them, and how you shared this data with stakeholders to drive actionable insights.

Discuss your experience in leveraging communication tools to facilitate collaboration. Share specific strategies you’ve implemented that have worked effectively in maintaining cohesion among team members in different time zones, possibly mentioning scheduling meetings or using collaborative platforms.

Share a detailed story that outlines the issue's impact on the project. Discuss your process of identifying, triaging, and communicating the resolution to stakeholders, emphasizing your problem-solving skills and teamwork.

Speak about the programming languages you are comfortable coding in and give examples of how you’ve used these skills in automated testing or building QA frameworks. Clarify how this proficiency has added value to your QA roles.

In your answer, highlight any resources, communities, or conferences you regularly engage with to keep your knowledge current. Mention any certifications or learning platforms that you have found particularly useful in your professional development.

Discuss the intricacies of QA within AI systems, like the unpredictability of model performance or data quality. Offer insights on approaches for addressing these challenges, such as implementing robust testing strategies that encompass both functional testing and performance validation.

Outline your strategy for fostering strong relationships with software engineers. Maybe discuss how you involve them early in the requirements phase and collaborate on defining clear acceptance criteria for the QA process.

Discuss the importance of gathering user feedback in enhancing product quality. Share examples of how user insights have influenced your testing plans or bug resolution strategies in previous roles, ultimately leading to better end-user experiences.

Explain your approach to documentation, emphasizing clarity and detail. Mention specific methods you’ve used for maintaining thorough documentation that ensures traceability and helps new team members onboard smoothly.