Foundation EGI
11 - 50 employees
Founded 2023
🏠Manufacturing
đź’Ľ Consulting
📦 Logistics
Manufacturing • Consulting • Logistics
Foundation EGI is an AI-driven platform that automates the generation of engineering documentation from 3D CAD data. The company converts assemblies into 2D/3D parts catalogs, GD&T technical drawings, optimized assembly sequences, and multilingual operator/service manuals, aiming to reduce manual drafting and speed product development for manufacturing and engineering teams. Foundation EGI positions itself as an enterprise SaaS solution that brings machine learning and computational design into industrial workflows to improve accuracy, traceability, and time-to-production.
ML Ops Engineer
Likely ghost job
đź•’ May 14
🍂 Massachusetts – Remote
⏰ Full Time
🟡 Mid-level
đźź Senior
🤖 Machine Learning Engineer
đź‘» Ghost score 76%
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Foundation EGI
11 - 50 employees
Founded 2023
🏠Manufacturing
đź’Ľ Consulting
📦 Logistics
Manufacturing • Consulting • Logistics
Foundation EGI is an AI-driven platform that automates the generation of engineering documentation from 3D CAD data. The company converts assemblies into 2D/3D parts catalogs, GD&T technical drawings, optimized assembly sequences, and multilingual operator/service manuals, aiming to reduce manual drafting and speed product development for manufacturing and engineering teams. Foundation EGI positions itself as an enterprise SaaS solution that brings machine learning and computational design into industrial workflows to improve accuracy, traceability, and time-to-production.
đź“‹ Description
• Utilize advanced AI, physics simulation, and computer graphics to reduce costs. • Improve engineering productivity across design and manufacturing processes.
🎯 Requirements
• BS in Computer Science or a related field. • 5+ years of experience as a AI/ML Ops, DevOps, Infrastructure Engineer or equivalent. • Expert-level Python and TypeScripts skills. • Experience with Docker, Kubernetes, Terraform, Google Cloud and AWS. • Deep understanding of machine learning models, including LLMs. • Experience designing and maintaining CI/CD pipelines to fine-tune or train ML models. • Excellent written and verbal communication skills.
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