Research Software Engineer – Geometry, ML & CAD Tools

CDFAM - Computational Design Symposium; United States; Remote; USD 130,000 - 210,000; Full time

Job summary

CDFAM - Computational Design Symposium seeks an experienced computational design researcher to advance geometry processing, simulation, and data-driven engineering tools. You will shape data pipelines, rendering components, and DSL-related workstreams in a cutting-edge research environment.

The role emphasizes building scalable Python-based services, large dataset management, and post-training ML workflows, with opportunities to influence DSL and compiler-related developments within the lab.

Qualifications

• PhD or MS focused on Computational Design, Simulation, or AI.
• 5+ years in Geometric Processing, Simulation, Optimization, ML, or DSLs.
• Proficiency writing clean, modular Python code.
• Experience with dataset creation and data pipelines.
• Experience developing CAD/CAM/CAE tools.
• Experience designing DSLs/compilers or tuning LLMs.

Responsibilities

• 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.

Skills

Geometric Processing

Simulation

Optimization

Machine Learning

Domain-Specific Languages

Education

PhD or MS in Computational Design/Simulation/AI

Tools

Python

CAD/CAE tools

LLMs tuning

Job description

CDFAM - Computational Design Symposium seeks an experienced computational design researcher to advance geometry processing, simulation, and data-driven engineering tools. You will shape data pipelines, rendering components, and DSL-related workstreams in a cutting-edge research environment.

The role emphasizes building scalable Python-based services, large dataset management, and post-training ML workflows, with opportunities to influence DSL and compiler-related developments within the lab.