Application Engineer, AI/ML

Lumafield•San Francisco, CA

8h•Hybrid

About The Position

Lumafield is seeking an experienced, customer-facing engineer with expertise in Machine Learning (ML) to assist customers in achieving business outcomes using CT-generated data. As an AI/ML Application Engineer, you will be responsible for developing, testing, and implementing machine learning models within customer engineering and manufacturing environments. These models will be applied to various use cases, including defect detection, dimensional analysis, anomaly detection, and process control. The role involves a blend of customer-facing responsibilities and internal platform development. For customers, you will define the scope of ML applications, build and validate models using their data, and deploy these models into their production workflows, both remotely and on-site. You will collaborate closely with Project Managers and other customer-facing teams, such as other Applications Engineers and Customer Success members. Internally, you will partner with Product Management and Software Engineering to transform recurring customer needs into product features and contribute to Lumafield's overarching AI/ML strategy across the platform.

Requirements

4+ years of professional experience building, including depth in applied computer vision, including model development and evaluation on image or volumetric data.
Hands-on experience taking ML models from training into production, including deployment, monitoring, and retraining (MLOps).
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.
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.

Nice To Haves

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.

Responsibilities

Develop, test, and deploy machine learning models using 2D and 3D CT data for customer inspection use cases.
Work directly with customer engineering and manufacturing teams, both remotely and on-site, to own the full model lifecycle, from data preparation, feature and label design, training, evaluation, and deployment to monitoring, and retraining.
Partner with Project Managers to scope customer ML deliverables, set realistic timelines, define success criteria, and communicate progress and risk.
Collaborate with Product Management and Software Engineering to translate recurring customer needs into product capabilities and support work to improve the broader Lumafield platform.
Contribute to Lumafield's internal AI/ML strategy, including model evaluation standards, deployment patterns, and governance across regulated industries.
Produce clear technical documentation, including model documentation, validation memos, and customer-facing reports.