Machine Learning Engineer

@ Layup Parts

Machine Learning Engineer

Posted today

About the job

Layup Parts develops manufacturing tech for aerospace, defense, and robotics, using automation and software to accelerate design, cost estimation, and data extraction.

Requirements

Experience training custom models
Advanced object detection experience
Geometry-based modeling experience
Worked with large datasets
Structured, spatial, or geometric data skills

Qualifications

Background in geometric or spatial data
Experience in object detection
CAD or manufacturing background
Strong data pipeline skills

Full job description

At Layup Parts, we're developing the technology that will build the future.

We're a manufacturing technology company replacing months of lead time with days, using proprietary software, automation, and advanced manufacturing systems built for speed. Our customers are inventing what's next, in aerospace, defense, robotics, and beyond. To keep up with them, manufacturing has to change. That's what we're building.

We're looking for a Machine Learning Engineer to train custom models using our internal data. This work spans design generation, cost estimation, evaluating the complexity and difficulty of a given design, and extracting structured data out of existing documentation. We're looking for someone who has trained custom models on large, parameter-rich datasets, ideally with a geometric or spatial component, and who is energized by problems in that space specifically.

What You'll Do

Train and iterate on custom ML models using Layup's internal manufacturing and design data

Build models that estimate cost and predict design complexity or manufacturing difficulty from part geometry

Develop models that generate or assist in generating new designs based on historical design data

Build pipelines to extract structured data (specs, dimensions, material callouts, etc.) from existing engineering documents and drawings

Evaluate and select modeling approaches suited to geometric, spatial, and other structured data, rather than text-based problems

Work closely with engineering and manufacturing teams to source, clean, and label internal datasets

Own model performance end-to-end, from data pipeline through training, evaluation, and deployment into internal tools

Continuously identify new opportunities where custom models could improve design, estimation, or manufacturing workflows

What We're Looking For

Experience training custom models beyond basic labeling or fine-tuning workflows

Experience with advanced object detection at minimum; data classification experience is a strong plus

Experience with geometry-based modeling is highly preferred

Experience working with large, parameter-rich datasets

Strongest fit is someone whose background is in structured, spatial, or geometric data problems rather than natural language or LLM-centric work

Bonus Points

Experience training geometry-specific models

CAD experience

Manufacturing experience

Equal Opportunity

Layup is an equal-opportunity employer. All qualified applicants will be treated with respect and receive equal consideration for employment without regard to race, color, creed, religion, sex, gender identity, sexual orientation, national origin, disability, uniform service, Veteran status, age, or any other protected characteristic per federal, state, or local law, including those with a criminal history, in a manner consistent with the requirements of applicable state and local laws, including the CA Fair Chance Initiative for Hiring Ordinance.

ITAR Requirements

To conform to U.S. Government export regulations, applicant must be a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (aka green card holder), (iii) Refugee under 8 U.S.C. § 1157, or (iv) Asylee under 8 U.S.C. § 1158, or be eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here.

Show full description

Similar jobs in Columbus, OH

See all Machine Learning Engineer jobs