ML Engineer - Optical Inspection

Job Description

Job Title: Machine Learning Engineer – Automated Optical Inspection. Location: Los Angeles County, CA

Responsibilities:

• Design and maintain platforms for developing, evaluating, and deploying machine learning models for real-world quantum hardware applications.
• Build and implement optical defect detection and classification models to support automated quality assurance in device manufacturing.
• Rapidly adopt emerging technologies, including Generative AI, to solve complex data exploration problems;
• Collaborate with fabrication scientists and engineers to develop data ingestion frameworks and generate actionable insights;
• Own the reliability and maintainability of the software stack, contributing to the development of scalable quantum computing technologies.
• Create active learning pipelines to enhance ML model performance using human feedback.

Qualifications:

• 3+ years of professional software development experience (non-internship).
• 2+ years of experience in system design, including design patterns, scaling, and reliability.
• Hands-on experience deploying computer vision models in production environments;
• Proven ability to build automation for large-scale problem-solving.

Preferred:

• MSc or PhD in a STEM field.
• 3+ years of experience across the full software development lifecycle.
• Background in working with researchers or scientists in a research setting.
• Experience with Infrastructure as Code tools (Terraform, CloudFormation, AWS CDK);
• Experience deploying and maintaining Retrieval-Augmented Generation (RAG) models and other generative AI systems.

Benefits / Additional:

• Competitive base pay ranging from $129,300 to $223,600 depending on geographic location and experience.
• Total compensation may include stock, sign-on bonus, medical, and financial benefits;
• Offers a diverse and inclusive team culture, with mentorship, learning, and career growth opportunities.
• Amazon provides workplace accommodations for individuals with disabilities.
• The position supports work-life balance, flexible work culture, and an employee-led inclusive environment.