Engineering Data Lead

We’re an MIT-born, venture-backed Silicon Valley startup building Engineering General Intelligence (EGI), an AI copilot for design and manufacturing. Our mission is to reinvent how physical products are designed and built, dramatically accelerating product development.

You will lead our Engineering Data team, the group that turns real-world engineering documentation into training and evaluation assets for EGI. Your focus is NPI and documentation flows: drawings, BOMs, ECOs, PPAPs, control plans, work instructions, service docs, and inspection criteria. You’ll define standards, ontologies, pipelines, and QA so our models learn to reason like organizations that ship hardware through change control. You’ll partner tightly with ML, product, and software, and scale delivery via contractors and vendors.

Responsibilities

• Own the data roadmap: strategy, milestones, and KPIs for engineering datasets and eval suites aligned to product goals
• Define standards & ontologies: modeling conventions, metadata/annotation schemas, GD&T acceptance, PPAP/AS9102 artifacts, and pass/fail criteria
• Build gold-standard packages: from CAD artifacts to full documentation sets (drawing bundles, BOMs, specs, WI/SOPs, inspection checklists) for training/benchmarking
• Operationalize change control: model ECR/ECO lifecycles, revisioning, traceability, and “as-designed / as-released / as-serviced” states across datasets
• Run scalable pipelines: SOPs, templates, data versioning, and release management; stand up QA gates and audits to prevent escapes
• Lead the team: mentor 3–6 ICs, manage vendors/contractors, conduct reviews, and raise the quality bar with objective metrics
• Partner with ML & Product: translate NPI use cases (e.g., drawing QA, tolerance checks, PPAP readiness) into representative datasets and evals; close the loop with results
• Automate where it helps: drive CAD/PLM scripting, parametric generation, and data tooling to speed throughput and improve consistency

What we're looking for

• Background in NPI or documentation-heavy engineering (Manufacturing/Process Eng, ME releasing to production, Technical Publications/Illustration, or PLM/Doc Control)
• Proven record of shipping real release packages (drawing sets, BOMs, PPAP, control plans, DFMEA/PFMEA, FAIRs/inspection reports, work instructions, service manuals)
• Working knowledge of GD&T (ASME Y14.x) and DFM/DFA applied to release-quality documentation
• Hands-on with major PLM/change control (Teamcenter, Windchill, Arena, etc.), ECR/ECO workflows, approvals, audit trails
• Comfort collaborating with ML/software teams; crisp documentation and cross-functional communication
• Leadership running SOP-driven pipelines and managing vendors/contractors with clear SLAs and QA criteria
• Obsessive about data quality: you notice edge cases, ambiguous callouts, and broken traceability

Bonus points

• CAD automation/parametric generation (NXOpen, Python, Creo macros, FreeCAD) for families of parts and drawing variants
• Experience defining ontologies/taxonomies for manufacturing/service concepts
• Familiarity with LLM/ML training loops, golden sets, and evaluation frameworks
• Exposure to PPAP / IATF 16949 / AS9102 or similar compliance regimes

Nice-to-have backgrounds

• Manufacturing/Process engineer who drove PPAPs and line bring-up
• Technical documentation/illustration lead for service manuals and parts catalogs
• PLM specialist who lived in ECR/ECO queues and audits
• ME/IE who owned releases at a hardware startup or tier-1 supplier

Get in touch: [email protected]