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 across multiple testing layers
Building and maintaining CI/CD pipelines for continuous integration and release validation
Developing test automation scripts and suites for software validation
Collaborating with cross-functional engineering teams to understand requirements and define test strategies
Defining quality metrics, KPIs, and release readiness criteria
Designing end-to-end system validation frameworks spanning hardware and software components
Performing root-cause analysis and investigation of system-level failures across multiple domains
Debugging and troubleshooting complex software and hardware integration issues
Creating internal tools and developer productivity platforms for testing and validation
Designing and executing stress testing, benchmarking, and failure mode analysis programs
Establishing standardized quality playbooks and testing best practices across engineering teams
Translating hardware specifications and system requirements into scalable test solutions
Building hardware-in-the-loop testing infrastructure and orchestration systems
Detecting and quarantining flaky tests and driving root-cause analysis with test owners
Automating commercial test equipment and instrumentation integration
Building domain knowledge in specialized technical areas such as CAE, CAD, robotics, or RF systems
Testing and validating machine learning software stacks and model execution
Leveraging artificial intelligence and agentic tools for intelligent test automation and validation
Validating non-deterministic AI products and voice agent systems in production environments
Operating in ambiguous environments and bringing structure to complex testing problems
Communicating technical status, risks, and quality signals to engineering stakeholders
Participating in design and code reviews with focus on testability and reliability
Mentoring junior team members and elevating quality practices across the organization
Owning and prioritizing test roadmaps aligned with product and engineering objectives
Reducing bug resolution time through joint triage and severity evaluation processes
Technology
The tools and technologies that define this role.
Open Jobs
70 open Quality Engineer jobs across 27 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.