Senior QA Engineer – Hybrid Accelerated AI

At Revvity, “impossible” is inspiration and “can’t be done” is a call to action. Revvity provides health science solutions, technologies, expertise, and services that deliver complete workflows from discovery to development, and diagnosis to cure. Revvity is revolutionizing what’s possible in healthcare, with specialized focus areas in translational multi-omics technologies, biomarkers identification, imaging, prediction, screening, detection and diagnosis, informatics and more. With more than $3 billion in revenue and over 11,000 employees, Revvity serves customers across pharmaceutical and biotech, diagnostic labs, academia, and governments. It is part of the S&P 500 index and has customers in more than 190 countries.

Revvity Signal Software, a Revvity company, provides solutions that are specialized scientific know‑how that empowers customers to gain critical insights from their data analytics and accelerate informed decisions. We deliver a comprehensive suite of software solutions to visualize and analyze critical data and help turn that data into actionable insights in an automated, predictive, and scalable way.

Our team is seeking a Senior QA Engineer – Hybrid Accelerated AI to join us in our efforts to continue empowering customers around the world.

Job Requirements

• AI / ML model validation : Design and execute comprehensive testing strategies specifically for AI and ML models, focusing on accuracy, robustness, and performance.
• Bias and fairness testing : Perform extensive testing to identify and mitigate biases or discriminatory outcomes in AI models, ensuring they adhere to ethical AI principles.
• Hybrid test execution : Balance the use of manual and automated testing methods. Perform manual exploratory testing on complex, non-deterministic AI outputs (e.g., Large Language Models) while building and maintaining automated suites for consistent regression testing.
• Automation framework development : Develop, maintain, and scale automated AI-based test cases using scripting languages such as Python or JavaScript. Integrate automated tests into our CI / CD pipelines to enable continuous model evaluation and rapid delivery.
• Data validation : Test data pipelines, feature engineering, and data quality to ensure models were trained on clean and reliable data.
• Edge‑case and adversarial testing : Create and execute test cases to challenge the AI model with edge cases and adversarial inputs to ensure safety and stability.
• Defect tracking and reporting : Identify, document, and track software and AI model defects with detailed, reproducible steps. Work with development teams to prioritize and resolve issues.
• Monitoring and metrics : Work with DevOps, QA leadership to configure monitoring tools and define metrics for tracking post‑deployment model health and detecting performance degradation or “model drift”.
• Continuous improvement : Stay up to date with emerging QA automation trends, AI testing methodologies, and tools. Propose and implement improvements to QA processes.

Basic Qualifications

Preferred Qualifications

The base salary range for this full‑time position is $100,000.00 to 120,000.00 USD . This range reflects the minimum and maximum target for a new hire in this position. The base pay actually offered to the successful candidate will take into account internal equity, work location, and additional factors, including job‑related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that base pay is only one part of our total compensation package and is determined within a range. This range allows for the successful candidate to have an opportunity to progress within the position and develop at our company. This base pay range does not take into account bonuses, equity, or other benefits which may be applicable and are dependent on the level and position offered.

What do we offer?

Learn more about Revvity’s benefits by visiting our Bswift page. Log‑In instructions are provided towards the bottom of the Bswift page.

#J-18808-Ljbffr