Application Engineer, CV/ML
On-siteSan Francisco, California, United States
Job Summary
Build, train, and validate computer-vision models on 2D and 3D CT data for customer inspection use cases including defect detection, dimensional analysis, and anomaly detection. Operate Lumafield scanners, perform analysis in Voyager, and present results to customers while owning the full model lifecycle from data preparation to deployment and monitoring. Partner with Project Managers to scope ML deliverables and collaborate with Product Management and Software Engineering to translate recurring customer needs into product capabilities. Produce clear technical documentation and build software components using modern AI tools.
Required Qualifications
- 3+ years of professional experience including hands-on work building and evaluating computer-vision models on image data including object detection, classification, labeling, and validation
- Comfortable seeing a model through the full lifecycle: data preparation, labeling, training, evaluation, and iteration based on real-world performance
- Experience working directly with customers or other non-ML stakeholders to translate business and engineering problems into ML solutions
- Comfort operating in engineering and manufacturing environments, including working with team members on the production floor
- Comfortable operating autonomously with a distributed team
- Strong written and verbal communication skills, including the ability to present technical results to engineering, product, and executive audiences
- A track record of shipping pragmatic, useful models — balancing speed, quality, and customer impact
- Willingness to travel approximately 30%, primarily to customer sites
- Background in industrial CT, computer vision on volumetric or 3D data, or NDT and inspection workflows
- Prior experience in a customer facing role such as Application Engineering, Solutions Engineering, or Forward Deployed Engineering role at a technical product company
- Familiarity with manufacturing data systems such as MES, SPC, or PLM, and the workflows surrounding them
- Experience contributing to internal AI/ML strategy or platform decisions at a previous company
- Domain experience in one of Lumafield's core industries: medical devices, aerospace and defense, automotive, electronics, or batteries
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