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

Foundation EGI•Boston, MA

About The Position

The Mechanical Data Engineer is an individual contributor on the Data Studio team at an MIT-born, venture-backed startup building Engineering General Intelligence (EGI), an AI copilot for design and manufacturing. The role transforms raw customer and internal engineering data into structured, high-fidelity datasets for model training, evaluation, inference, and customer delivery. It combines mechanical engineering and manufacturing expertise with hands-on data creation, workflow design, and quality assurance. Mechanical engineering or manufacturing design experience is essential. The engineer creates CAD reference models and other engineering artifacts that represent authoritative ground truth, establishes dataset quality standards, and collaborates with product, research, engineering, and customer-facing teams. The role also supports customers in preparing datasets and schemas, reviews external contractor work, and helps maintain scalable, repeatable data processes.

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 such as Creo Illustrate, Adobe Illustrator, or Arbortext.
Ability to interpret complex mechanical assemblies, technical drawings, GD&T, and engineering documentation.
Experience creating artifacts such as exploded views, work-step sequences, repair manuals, or manufacturing instructions.
Strong problem-solving skills and ability to translate domain workflows into structured data requirements.
Excellent communication and cross-functional collaboration skills.

Nice To Haves

Experience with data operations, labeling workflows, ML data pipelines, or the AI/ML data lifecycle, including collection, labeling, QA, training, evaluation, and deployment.
Experience in fast-paced startup or high-growth environments.
Comfort with customer-facing discovery or solutioning.

Responsibilities

Ingest, clean, transform, and structure customer and internally generated engineering data for AI training and inference.
Build mechanical components and assemblies in CAD as authoritative ground truth for evaluating and training AI systems.
Create labeled datasets, reference designs, annotations, exploded views, sequences, and other engineering artifacts.
Use engineering judgment to define and assess dataset quality, and maintain standards for metadata, annotation, and model quality.
Collaborate with Product Managers on annotation, data correction, model-output review, and pipeline automation tools.
Provide feedback on tool usability, workflow efficiency, and automation opportunities; help develop scalable, repeatable data processes.
Work with engineering and research teams to understand data requirements, model failure modes, and gaps requiring new data.
Supply representative engineering examples and ground-truth mechanical designs to influence model behavior.
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.
Create technical documentation, exploded views, sequences, and annotations that encode engineering reasoning into training data.
Ensure datasets reflect real-world constraints, design-for-manufacturing considerations, material behavior, and industry best practices.
Work with customers to understand data sources, schemas, formats, and quality expectations; guide dataset preparation and pipeline improvements.
Communicate progress and surface risks or issues early to support delivery timelines.
Review and work with external contractors, ensuring output quality and adherence to SOPs.