Mechanical Data Engineer – Mechanical Data Exp Required
Foundation EGI
full-time
Posted on:
Location Type: Remote
Location: Massachusetts • United States
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About the role
- Ingest, clean, transform, and structure customer and internally generated engineering data for AI training and inference.
- Design and build high-quality mechanical components and assemblies in CAD to serve as authoritative ground truth for evaluating and training AI systems.
- Produce labeled datasets, reference designs, annotations, exploded views, sequences, and other engineering artifacts that encode real-world reasoning.
- Apply engineering judgment to define and assess output quality across datasets.
- Continuously refine standards for metadata, annotation, and model quality, maintaining a living “definition of quality” for ME datasets.
- Collaborate with Product Managers to shape tooling used for annotation, data correction, model-output review, and pipeline automation.
- Provide detailed feedback on tool usability, workflow efficiency, and automation opportunities.
- Help develop scalable, repeatable data processes that improve throughput and data consistency.
- Partner closely with engineering and research teams to understand model data requirements, failure modes, and areas needing new data.
- Influence model behavior by supplying representative engineering examples and ground-truth mechanical designs.
- Partner with customer-facing teams to translate domain requirements, industry standards, and customer data schemas into actionable dataset specifications.
- Serve as a subject matter expert on mechanical engineering formats, CAD standards, manufacturing practices, and design artifacts.
- Generate technical documentation, exploded views, sequences, and annotations that encode engineering reasoning into training data.
- Ensure that datasets reflect real-world constraints, DFM (Design for Manufacturing) considerations, material behavior, and industry best practices.
- Embed engineering reasoning into training data so that AI systems learn not just geometry or text, but engineering intent.
- Work with customers to understand their data sources, schemas, formats, and quality expectations.
- Guide customers in preparing high-quality datasets, defining structured schemas, and improving data pipelines.
- Support delivery timelines by communicating progress clearly and surfacing risks or issues early.
- Review and work with external contractors, ensuring high-quality output and adherence to SOPs.
Requirements
- Strong domain expertise in mechanical engineering, manufacturing design, or industrial workflows.
- Hands-on experience with CAD tools such as SolidWorks, CATIA, Siemens NX, or Creo.
- Familiarity with annotation tools and illustration software (e.g., Creo Illustrate, Adobe Illustrator, Arbortext).
- Ability to interpret complex mechanical assemblies, technical drawings, GD&T, and engineering documentation.
- Experience creating artifacts like exploded views, work-step sequences, repair manuals, or manufacturing instructions.
- Strong problem-solving skills and the ability to translate domain workflows into structured data requirements.
- Excellent communication and cross-functional collaboration skills.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
CADmechanical engineeringmanufacturing designannotationdata processingGD&Tdata pipelinesdata quality assessmenttechnical documentationdata transformation
Soft Skills
problem-solvingcommunicationcollaborationengineering judgmentfeedback provisionworkflow efficiencycustomer guidanceinfluencedata consistencyquality definition