Foundation EGI

Software Engineer

• Serve as the primary subject-matter expert on automotive assembly sequence planning, tooling, and production line setup.
• Define and review product workflows and requirements for sequence planning, torque specs, tooling selection, ergonomic risks, and MTM or time study use.
• Provide practical guidance on new or modified production lines, including station layout, work content, standardized work, and work instructions.
• Define and review how assembly tools, fixtures, ergonomic aids, and error-proofing devices are represented and used in the software.
• Write clear product specifications and user-facing documentation such as workflows, examples, and best-practice guides.
• Validate that the product behavior and algorithms match real plant workflows and provide feedback from pilot use and customer discussions.

Senior Manufacturing Engineering Consultant – Automotive Assembly Planning

Data Engineer

• 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.
• Continuously refine standards for metadata, annotation, and model quality, maintaining a living “definition of quality” for ME datasets.
• Collaborate with Product Managers to shape tooling used for annotation, data correction, model-output review, and pipeline automation.
• Provide detailed feedback on tool usability, workflow efficiency, and automation opportunities.
• Help develop scalable, repeatable data processes that improve throughput and data consistency.
• Partner closely with engineering and research teams to understand model data requirements, failure modes, and areas needing new data.
• Influence model behavior by supplying representative engineering examples and ground-truth mechanical designs.
• Partner with customer-facing teams to 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 that encode engineering reasoning into training data.
• Ensure that datasets reflect real-world constraints, DFM (Design for Manufacturing) considerations, material behavior, and industry best practices.
• Embed engineering reasoning into training data so that AI systems learn not just geometry or text, but engineering intent.
• Work with customers to understand their data sources, schemas, formats, and quality expectations.
• Guide customers in preparing high-quality datasets, defining structured schemas, and improving data pipelines.
• Support delivery timelines by communicating progress clearly and surfacing risks or issues early.
• Review and work with external contractors, ensuring high-quality output and adherence to SOPs.

Mechanical Data Engineer – Mechanical Data Exp Required

Senior Manufacturing Engineering Consultant – Process Planning Expert

Mechanical Engineer

• Own the full sales cycle for Enterprise customers - from outbound prospecting to solutioning to closing and handoff.
• Help achieve quarterly customer and revenue targets
• Lead detailed technical conversations with the customers to understand their pain points.
• Translate them into customized sales proposals (POCs, pilots, commercial) with the requisite level of technical and commercial granularity.
• Own the delivery of the pilot projects for a very technical product ensuring that they successfully lead to a subscription.
• Be the voice of the customer with the internal product and R&D teams.
• Draft and communicate technical requirements for them to ensure your customer needs are correctly translated internally.
• Always looking for ways to improve the sales process and decrease the time to close.
• Mentor and hire future team members as we scale

Sales Engineer – Mechanical Engineering, GTM Manufacturing

Backend Engineer

• Design, develop, and maintain backend services and scripts using Python.
• Integrate our product with 3rd-Party design solutions, like Siemens NX, CATIA, or PTC.
• Design, develop, and maintain data models using Protobuf.
• Collaborate with cross-functional teams, including product managers, engineers and researchers.
• Write clean, well-documented, fast, and maintainable code.

Senior Backend Engineer – 3D Data, CAD Automation

• Own the definition and evaluation of output quality, ensuring consistency and accountability across all internal and external datasets.
• Oversee ingestion, cleaning, transformation, and structuring of customer data for AI model training and inference.
• Build scalable processes and frameworks for data labeling, annotation tools, quality checks, and feedback loops.
• Ensure timely, high quality data delivery for internal R&D and customer deployments.
• Own SLAs, accuracy targets, and “definition of quality” for all datasets.
• Partner with Product Managers to shape data-related features, workflows, and tooling (e.g., annotation UI, correction UI, model output review tools).
• Translate customer needs into clear data requirements and repeatable solutions.
• Build and lead a Data Studio team.
• Implement best practices for documentation, quality metrics, repeatable workflows, and compliance.
• Drive continuous improvements in throughput, cost efficiency, and accuracy.
• Work closely with engineering and research teams to define data needs for model training, evaluation, and debugging.
• Collaborate with BD team to scope data requirements for onboarding and implementation.
• Serve as the subject matter expert on data quality, data formats, labeling standards, and customer specific nuances related to manufacturing design.
• Interface with customers to understand their domain, data structures, and quality expectations.
• Guide customers through data preparation, schema definition, and ongoing iteration.
• Own delivery timelines, reporting, and communication for all active data projects.

Lead Data Architect – Manufacturing Design

• 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.