Senior Engineer, AI Systems Test

Danaher•Vista, CA

2d•Onsite

About The Position

The Senior Engineer, AI Systems Test is responsible for ensuring the quality, reliability, and performance of AI-driven digital pathology solutions. You will collaborate with cross-functional teams including Deep Learning scientists, software developers, and system engineers to design and implement robust verification strategies. This role emphasizes automation, system integration, and performance testing in a regulated environment. You will act as a resource for less experienced colleagues and may lead small projects with manageable risks and resource requirements.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, or a related field, or equivalent industry experience.
6+ years of experience in software testing or software development, preferably within a regulated industry.
Strong programming and scripting skills in languages such as Python, PowerShell, JavaScript, or R, with proficiency in Linux and Windows command-line environments.
Experience with test automation and DevOps practices, including frameworks such as PyTest, Selenium, Cypress, or Postman, and CI/CD tools and methodologies.

Nice To Haves

Experience with cloud platforms, containerization, orchestration technologies, and enterprise IT infrastructure (AWS, Azure, Docker, Kubernetes).
Knowledge of medical device development, regulatory compliance, design controls, and cybersecurity standards.
Experience with AI/ML technologies, model validation, and digital pathology or healthcare diagnostic workflows.

Responsibilities

Develop, execute, and automate testing strategies for AI-based systems, including test plans, manual and automated test cases, performance testing, and integration of automated tests into CI/CD pipelines to ensure system quality, scalability, and regulatory compliance.
Collaborate with engineering and product teams throughout the development lifecycle to define requirements, establish acceptance criteria, assess quality risks, and improve system testability through design reviews and continuous feedback.
Manage and validate AI/ML datasets and system performance, including curating large datasets used for training, testing, and validation, while identifying and resolving complex issues across software, hardware, and AI system components.
Drive quality excellence and technical leadership by enhancing QA processes, tools, and best practices, and mentoring software AI test engineers to support team growth and organizational success.