Vinci
Procedural Data Generation Engineer
$170K–$230K
Palo Alto HQ · Hybrid · Full-time · Posted Jun 24, 2026
- Experience
- Hiring across levels from strong mid-level through staff; no years specified.
About the job
Build systems that generate diverse, physically valid synthetic geometries and simulation configurations for training and evaluating physics models.
What you'll do
- Build procedural generators for parametric, hardware-like geometry.
- Generate physically plausible simulation configurations, including boundary conditions, materials, and loading scenarios.
- Measure generated-data diversity and coverage and relate dataset composition to model performance.
What they ask for
- Software engineering skills, especially in Python.
- Hands-on experience with programmatic or parametric geometry.
- Solid geometry processing fundamentals, including meshing, boolean operations, and voxelization or rasterization.
- Ability to reason about physical validity.
Nice to have
- Exposure to ML training pipelines and how dataset composition affects model behavior.
- Familiarity with LLM-driven code generation, FEA or thermal engineering, quality-diversity algorithms, open endedness, deep learning fundamentals, or hardware or semiconductor design.
Pay
$170K – $230K (base salary; currency not specified)
Tools
Python, CadQuery, OpenCascade, Build123d
AI focus
Generate synthetic training and evaluation data for physics AI models; connect dataset diversity and composition to model performance.
Model-written summary · the original posting is authoritative