Job Description:
• 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.
Benefits: