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Mid LevelFull-timeRustAI
About the Role
We are seeking a Data Engineer to join our Data Studio team, focusing on building and scaling data pipelines, tooling, and workflows for AI systems in design and manufacturing. This hands-on role involves transforming raw customer data into structured datasets to power model training, evaluation, and delivery, requiring strong mechanical engineering expertise.
Key Responsibilities
- →Ingest, clean, transform, and structure engineering data for AI training and inference
- →Design and build high-quality mechanical components and assemblies in CAD for ground truth evaluation
- →Produce labeled datasets, reference designs, annotations, and engineering artifacts
- →Apply engineering judgment to define and assess output quality across datasets
- →Collaborate with Product Managers to shape annotation, data correction, and automation tooling
- →Partner with engineering and research teams to understand model data requirements and failure modes
- →Generate technical documentation, exploded views, and annotations to encode engineering reasoning
- →Work with customers to understand data sources, schemas, formats, and quality expectations
- →Guide customers in preparing high-quality datasets and improving data pipelines
- →Review and work with external contractors to ensure 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 like Creo Illustrate, Adobe Illustrator, or 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 ability to translate domain workflows into structured data requirements
- ✓Excellent communication and cross-functional collaboration skills
- ✓Preferred: 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
