Backend Engineer - 3D Geometry & Manufacturing Infra

Hyle Industries; Marietta (GA); Sur place; USD 90 000 - 140 000; Plein temps

Avantages offerts par ce poste

Relocation assistance

Health, dental, and vision coverage

Résumé du poste

Hyle Industries in Marietta, GA is building intelligence-native infrastructure for manufacturing. You will own the backend that reads, repairs, and analyses 3D models at scale, and you will connect the geometry pipeline to services and the machines on the shop floor.

You will work across code and hardware, owning the architecture, and building the tooling for mesh repair, feature detection, and DFM analysis, while applying machine learning to manufacturability and cost decisions.

Qualifications

• Fluency in Python or another backend language.
• Experience manipulating 3D models in code: mesh repair, feature detection, and formats STEP, STL, 3MF.
• Experience building and consuming APIs, and building command line tools.
• Comfort standing up and running Linux servers.

Responsabilités

• Build and own the services that process, analyse, and repair 3D models at scale.
• Develop tooling for mesh repair, feature detection, and DFM analysis across processes (milling, turning, waterjet, additive).
• Apply machine learning to geometry where it adds value: manufacturability, process selection, cost.
• Design and ship the API, SDK, CLI, and MCP surfaces, and the Linux infrastructure under them.
• Own the architecture and the technical decisions; you decide how it gets built and you make it work.

Connaissances

Python

3D models

APIs

Linux

Outils

STEP

STL

3MF

Description du poste

Hyle Industries in Marietta, GA is building intelligence-native infrastructure for manufacturing. You will own the backend that reads, repairs, and analyses 3D models at scale, and you will connect the geometry pipeline to services and the machines on the shop floor.

You will work across code and hardware, owning the architecture, and building the tooling for mesh repair, feature detection, and DFM analysis, while applying machine learning to manufacturability and cost decisions.