Mechanical Data Engineer (Mechanical + Data Engineering Required) 3 Month Contract Role

Foundation EGI is building an AI copilot for product design and manufacturing. The Mechanical Data Engineer transforms engineering data into high-quality datasets, CAD reference designs, and workflows that support AI model training, evaluation, and customer delivery.

Responsibilities:

• 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
• Experience with data operations, labeling workflows, ML data pipelines, or AI/ML data lifecycle (collection -> labeling -> QA -> training -> evaluation -> deployment)
• Experience in fast-paced startup or high-growth environments
• Comfort with customer-facing discovery or solutioning