Staff Machine Learning Quality Engineer

Company Description

It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone.

Job Description

Job Title: Staff QA Engineer in Machine Learning
Location: Santa Clara, CA 

ServiceNow is changing the way people work. With a service-orientation toward the activities, tasks and processes that make up day-to-day work life, we help the modern enterprise operate faster and be more scalable than ever before. 

We’re disruptive.  We work hard but try not to take ourselves too seriously.  We are highly adaptable and constantly evolving.  We are passionate about our product, and we live for our customers.  We have high expectations and a career at ServiceNow means challenging yourself to always be better. 

What you get to do in this role:

As part of the ServiceNow's Machine Learning Quality Engineering team, work on AI/ML-specific test strategies, and build testing frameworks. Opportunity to learn, work and contribute to the innovative and enterprise grade ServiceNow’s Natural Language Understanding and Artificial Intelligence engine as part of the overall offering.
Experience with instrumentation and performance profiling of systems with large memory requirements and tight response tolerances.

• Take ownership of end-to-end quality deliverables for ML/AI products.
• Act as the voice of quality, collaborating with Product and Development teams to define comprehensive test strategy while establishing and adhering to quality milestones, and execute according to plan.
• Evaluate the quality, accuracy, performance, and safety of AI-generated content produced by LLMs and identify weaknesses
• Create and maintain test automation frameworksPartner with labeling teams to drive data creation processes/validation
• Collect, analyze, and report quality metrics from test execution and create defects based on results patterns.
• Contribute to refining evaluation criteria and methodologies for model assessment to improve AI evaluation frameworks
• Coordinate with engineering organizations in troubleshooting or addressing issues with applications and dev/test environments.
• Stay up to date with latest developments in LLMs and AI ethics to improve evaluation techniques

Qualifications

In order to be successful in this role, we need someone who has:

• Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry.
• 8+ years of professional experience in software quality engineering, with a strong focus on AI and machine learning
• Deep, hands-on experience testing machine learning and generative AI systems, including validating model predictions and conducting end-to-end workflow integration testing
• Strong knowledge of synthetic data generation and prompt engineering to support robust model evaluation
• Expert-level understanding of AI principles, including agentic AI, algorithms, models, and responsible AI/ethics
• Proficient in multiple automated testing frameworks such as Java, JUnit, Selenium, TestNG, and other open-source tools
• Proven ability to lead quality efforts within Agile scrum teams, guiding QE engineers and collaborating cross-functionally
• Skilled at diagnosing and resolving complex issues, with a focus on root cause analysis (RCA) and long-term solutions
• Demonstrated ability to implement best practices and coding standards across tools, frameworks, and design patterns
• Fluent in Java and Python, with strong scripting skills for test automation and process optimization
• In-depth experience applying a wide range of testing techniques (unit, integration, performance, automation) and choosing the right one for the task
• Expert user of development tools such as IDEs, debuggers, build tools, source control systems, profilers, and Unix/system admin tools
• Familiar with ServiceNow instances and their integration in quality engineering workflows
• Solid experience working within Agile development environments, ensuring quality is embedded across the SDLC
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