Foundation EGI

Research Scientist

• 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.

Research Scientist – Geometry, Machine Learning

Machine Learning Engineer

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

ML Ops Engineer

Full-stack Engineer

Research & Development Software Engineer – Geometry, AI

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 Engineering

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 CAD Backend Engineer – Mechanical, CAD Automation, CAD API Expertise

Research Software Engineer – ML for Manufacturing, Computational Design, Geometry Processing

AI Engineer

Applied AI Engineer – ML for Manufacturing, Computational Design, Geometry Processing

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.