Quality Engineer
Engineers in this role focus on testing and validating complex AI software systems across domains like machine learning frameworks, inference platforms, and autonomous systems. They design automated test frameworks, build CI/CD infrastructure, and collaborate with engineering teams to ensure AI products meet stringent quality and performance standards. What distinguishes them is their emphasis on systems-level thinking—they architect scalable testing solutions that handle the unique challenges of AI workloads, from ML model accuracy validation to hardware-software integration testing. These engineers typically sit within larger quality or systems teams in AI-focused companies, working cross-functionally with ML engineers, infrastructure teams, and product owners to accelerate development velocity while maintaining reliability and safety.
Skills
What companies are looking for in this role.
Designing and implementing automated test frameworks and infrastructure
Developing and maintaining test automation across large codebases and complex systems
Creating and executing test plans and test procedures for software validation
Analyzing test data and generating actionable insights from test results
Debugging and troubleshooting test pipeline failures and infrastructure issues
Performing root cause analysis and identifying resolution strategies for quality issues
Designing and optimizing CI/CD pipelines for test execution and reliability
Translating system specifications and requirements into automated test suites
Developing tooling and internal platforms that improve developer productivity and engineering velocity
Testing complex distributed and multi-tiered backend systems
Writing performance test plans and monitoring frameworks for system evaluation
Applying systems engineering principles including requirements definition and formal verification
Managing data-driven testing strategies and developing observability across test systems
Designing hardware validation and qualification frameworks for physical systems
Optimizing test execution efficiency and improving validation methodologies
Coordinating verification and validation campaigns for complex autonomous systems
Implementing machine learning models and AI-driven tools to enhance testing and quality assurance
Leveraging AI-powered insights and data-driven approaches to proactively identify quality issues
Bridging software capabilities with operational execution to enable scaled deployment
Collaborating with cross-functional teams including hardware, software, and systems engineers
Communicating technical findings, risks, and recommendations to engineering stakeholders
Leading retrospectives and driving continuous improvement initiatives to reduce technical debt
Operating in ambiguous environments and bringing structure to complex problems
Establishing testing best practices, standards, and processes across engineering organizations
Mentoring and providing technical direction to team members on quality practices
Technology
The tools and technologies that define this role.
Open Jobs
64 open Quality Engineer jobs across 16 companies.
Other Engineering roles
General-purpose software engineering roles focused on building and maintaining software systems. Covers generalist SWE positions that don't clearly fall into frontend, backend, fullstack, or other specialized tracks.
Engineers focused on server-side systems, APIs, services, and data processing pipelines. Includes roles explicitly labeled as backend or server-side development.
Engineers specializing in user-facing interfaces, web applications, and client-side development. Includes UI/UX engineering and web development roles.
Engineers working across the entire application stack, handling both frontend and backend responsibilities.
Engineers building and maintaining internal platforms, cloud infrastructure, compute systems, and developer tooling.