Customer-Facing CV/ML Engineer for CT Inspection

Lumafield; San Francisco (CA); Hybrid; USD 120,000 - 140,000; Full time

Benefits offered by this job

Health & wellness stipend

401k

Parental leave

Flexible PTO

Commuter benefits

Company wide events

Job summary

Lumafield is seeking an ML-experienced, customer-facing engineer to help customers achieve business results with CT-generated data. As a CV/ML Application Engineer, you will develop, test, and implement machine learning models inside customer engineering and manufacturing environments — for defect detection, dimensional analysis, anomaly detection, and process control.

The role combines customer-facing work with internal platform development.

Qualifications

• 3+ years of professional experience building and evaluating computer-vision models on image data.
• Experience taking models through full lifecycle: data preparation, labeling, training, evaluation, deployment.
• Experience working with customers or non-ML stakeholders to translate problems into ML solutions.
• Comfort operating in engineering/manufacturing environments and with distributed teams.
• Willingness to travel approximately 30% to customer sites.

Responsibilities

• Build, train, and validate computer-vision models on 2D and 3D CT data for customer inspection use cases.
• Develop deep working knowledge of Voyager and the Lumafield platform, and apply it to build and deliver customer solutions.
• Operate Lumafield scanners, perform Voyager analysis, and present results to customers.
• Scope ML deliverables with Project Managers and define success criteria, timelines, and risks.
• Collaborate with Product Management and Software Engineering to translate recurring customer needs into product capabilities.

Skills

Computer vision

Object detection

Image analysis

Customer-facing

Model lifecycle

Job description

Lumafield is seeking an ML-experienced, customer-facing engineer to help customers achieve business results with CT-generated data. As a CV/ML Application Engineer, you will develop, test, and implement machine learning models inside customer engineering and manufacturing environments — for defect detection, dimensional analysis, anomaly detection, and process control.

The role combines customer-facing work with internal platform development.