Lead AI Quality Engineer – Medical Device SaMD

Danaher Corporation; Vista (CA); On-site; USD 160,000 - 180,000; Full time

Benefits offered by this job

Benefits package

Job summary

Leica Biosystems, a Danaher operating company, is seeking an AI Quality Engineer to lead QA efforts for AI/ML medical device software, ensuring safety, regulatory alignment and product quality. This on-site role reports to the Director of QA and Regulatory Compliance in Vista, CA.

You will partner with R&D, regulatory, and clinical teams, mentor junior engineers, and drive risk management and V&V activities across the AI/ML lifecycle to uphold rigorous standards and continuous improvement.

Qualifications

• Experience with AI/ML algorithms, model validation and regulated software/dev.
• Proven ability to lead AI-focused risk management and quality processes.
• Strong leadership, project management and communication skills across AI/ML, Digital Health, Cybersecurity.

Responsibilities

• Represent the Quality Engineering function on cross-functional teams, contributing to design controls and DHF development.
• Lead AI/ML quality assurance strategies aligned with FDA, MDR, IVDR and ISO standards.
• Partner with data scientists, software engineers and clinical experts to meet regulatory and performance expectations.
• Support regulatory submissions such as FDA pre-sub, 510(k) and IVDR CE while driving AI/ML risk management.
• Lead lifecycle quality activities including V&V, CAPA, audits, and mentoring junior engineers.

Skills

AI/ML expertise

Regulatory knowledge

Leadership

Cross-functional collaboration

Education

Bachelor’s or Master’s in CS/DS/AI

Job description

Leica Biosystems, a Danaher operating company, is seeking an AI Quality Engineer to lead QA efforts for AI/ML medical device software, ensuring safety, regulatory alignment and product quality. This on-site role reports to the Director of QA and Regulatory Compliance in Vista, CA.

You will partner with R&D, regulatory, and clinical teams, mentor junior engineers, and drive risk management and V&V activities across the AI/ML lifecycle to uphold rigorous standards and continuous improvement.