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Foundation EGICore Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in mechanical engineering and CAD design, with a strong focus on data processes for AI training and inference. Capable of translating complex engineering requirements into structured datasets while ensuring quality and adherence to industry standards.
Highest-signal resume keywords
Mechanical Engineering ExpertiseCAD Tools ProficiencyData Operations ExperienceAnnotation Tools FamiliarityProblem-Solving Skills
About the role
Key responsibilities & impact- Ingest, clean, transform, and structure customer and internally generated engineering data for AI training and inference
- Design and build mechanical components and assemblies in CAD as authoritative ground truth for evaluating and training AI systems
- Produce labeled datasets, reference designs, annotations, exploded views, sequences, and other engineering artifacts
- Define and assess output quality across datasets and maintain standards for metadata, annotation, and model quality
- Collaborate with Product Managers on annotation, data correction, model-output review, and pipeline automation tooling
- Provide feedback on tool usability, workflow efficiency, and automation opportunities
- Develop scalable, repeatable data processes that improve throughput and data consistency
- Partner with engineering and research teams to understand model data requirements and failure modes
- 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
- Generate technical documentation, exploded views, sequences, and annotations encoding engineering reasoning into training data
- Ensure datasets reflect real-world constraints, DFM considerations, material behavior, and industry best practices
- Work with customers to understand data sources, schemas, formats, and quality expectations
- Guide customers in preparing datasets, defining structured schemas, and improving data pipelines
- Communicate progress clearly, surface risks early, and review external contractors for quality and SOP adherence
Requirements
What you’ll need- 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 (preferred)
- Experience in fast-paced startup or high-growth environments (preferred)
- Comfort with customer-facing discovery or solutioning (preferred)
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Mechanical EngineeringCAD DesignData ProcessingAnnotation WorkflowsTechnical DocumentationGD&T InterpretationExploded Views CreationManufacturing InstructionsData Quality AssessmentML Data Lifecycle
Soft Skills
Communication SkillsCross-Functional CollaborationProblem-Solving
Tools & Technologies
SolidWorksCATIASiemens NXCreoCreo IllustrateAdobe IllustratorArbortext
Industry Keywords
Manufacturing DesignIndustrial WorkflowsData Quality StandardsEngineering DocumentationCustomer Data Schemas