Applied Data Architect – Manufacturing
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Job Description
Build and scale data pipelines for AI Copilot in design and manufacturing at a venture-backed startup. Transform raw customer data into structured datasets with mechanical engineering expertise.
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.
- Collaborate with Product Managers to shape tooling used for annotation, data correction, model-output review, and pipeline automation.
- Partner closely with engineering and research teams to understand model data requirements, failure modes, and areas needing new data.
- Work with customers to understand their data sources, schemas, formats, and quality expectations.
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.
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