Foundation EGI

• You'll help build systems that: - Translate CAD models into machine-readable engineering data. - Connect Siemens NX, CATIA, SOLIDWORKS and other CAD platforms with cloud-native AI services. - Build scalable APIs that allow engineering applications to exchange geometry and metadata. - Develop Python services that automate complex engineering workflows. - Design backend systems that manage CAD assemblies, parts, configurations and engineering metadata. - Partner with researchers building next-generation Engineering AI.

• Design, develop, and maintain geometry processing and simulation algorithms for engineering applications. • Build services for reading, processing, and writing 2D/3D engineering data. • Develop rendering modules for generating 2D/3D visual assets. • Curate and manage large-scale datasets for learning-based systems. • Implement and optimize post-training workflows for machine learning models. • Contribute to the development of domain-specific languages for engineering tasks.

• You'll help build systems that: • Translate CAD models into machine-readable engineering data. • Connect Siemens NX, CATIA, SOLIDWORKS and other CAD platforms with cloud-native AI services. • Build scalable APIs that allow engineering applications to exchange geometry and metadata. • Develop Python services that automate complex engineering workflows. • Design backend systems that manage CAD assemblies, parts, configurations and engineering metadata. • Partner with researchers building next-generation Engineering AI.

• Design, develop, and maintain geometry processing and simulation algorithms for engineering applications. • Build services for reading, processing, and writing 2D/3D engineering data. • Develop rendering modules for generating 2D/3D visual assets. • Curate and manage large-scale datasets for learning-based systems. • Implement and optimize post-training workflows for machine learning models. • Contribute to the development of domain-specific languages for engineering tasks.

• Utilize advanced AI, physics simulation, and computer graphics to reduce costs. • Improve engineering productivity across design and manufacturing processes.

• Design, develop, and maintain geometry processing and simulation algorithms for engineering applications. • Build services for reading, processing, and writing 2D/3D engineering data. • Develop rendering modules for generating 2D/3D visual assets. • Curate and manage large-scale datasets for learning-based systems. • Implement and optimize post-training workflows for machine learning models. • Contribute to the development of domain-specific languages for engineering tasks.

• 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.

• 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.

We are an MIT-born, venture-backed Silicon Valley startup building a real-life 'Jarvis'. An AI Copilot for design and manufacturing. Our goal is to utilize advanced AI, physics simulation, and computer graphics to reduce costs and improve engineering productivity across all steps of the design and manufacturing process. Overview: Foundation EGI is looking for an experienced Manufacturing or Industrial Engineering Consultant with deep automotive experience in planning and documenting new production lines, especially final assembly operations. This person will serve as a domain expert for a software product focused on assembly sequence and tooling planning bringing real-world shop floor experience into the product design, requirements, and documentation. You should be an industry veteran who has led or supported the planning of new or modified production lines at OEMs or Tier 1 suppliers: -Assembly sequence planning -Selection and specification of assembly tools and equipment -Torque specification and tightening strategies -Ergonomic risk assessment -MTM and time studiesProduction documentation and launch readiness Responsibilities - 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. You'll Thrive with - 10 or more years of experience in manufacturing or industrial engineering roles within automotive OEM or Tier 1 suppliers. - Proven experience planning and launching new or significantly modified production lines, especially final assembly. Hands-on experience with: - Assembly sequence planning and operation breakdown. - Tool and equipment selection for assembly operations, including torque tools, fixtures, and ergonomic assists. - Torque specifications and fastening process design, including DC tools, tightening strategies, and traceability. - Ergonomic risk assessment using methods such as REBA, RULA, or NIOSHMTM, MOST, or equivalent time study methods. - Strong written and verbal communication skills and the ability to clearly explain complex manufacturing and tooling concepts to non-experts such as software engineers.

• Design, develop, and maintain geometry processing and simulation algorithms for engineering applications. • Build services for reading, processing, and writing 2D/3D engineering data. • Develop rendering modules for generating 2D/3D visual assets. • Curate and manage large-scale datasets for learning-based systems. • Implement and optimize post-training workflows for machine learning models. • Contribute to the development of domain-specific languages for engineering tasks.