Vinci4D.ai

Vinci4D.ai

Procedural Data Generation Engineer

Palo Alto HQ

Sponsorship not specifiedDetected 27 days ago
PythonAlgorithmsMachine LearningDeep LearningLLMsFEAHardware Design

About the role

  • The quality of our models is bounded by the quality and diversity of the data they're trained on, and that data doesn't exist in the wild.
  • This is a deep technical role at the intersection of computational geometry, physics simulation, and machine learning.

Responsibilities

  • Design and build procedural generators for parametric, hardware-like geometry using programmatic CAD (e.g., CadQuery, OpenCascade, Build123d) or another tool of your choice.

Requirements

  • Hands-on experience with programmatic/parametric geometry: scripted CAD, B-rep and mesh representations, SDFs, or procedural generation in graphics tools.
  • Comfort reasoning about physical validity - you don't need to be a simulation expert, but you should care whether a boundary condition makes sense.
  • Software engineering skills, especially in Python
  • Solid geometry processing fundamentals: meshing, boolean operations, voxelization/rasterization, and their numerical pitfalls.

Nice to have

  • Familiarity with LLM-driven code generation.
  • FEA or thermal engineering experience.
  • We're hiring across levels from strong mid-level through staff.
  • Your work is crucial to the company's success.
  • Work alongside researchers and engineers spanning ML, numerical methods, and hardware engineering on the frontier of AI.

Benefits

  • Define and measure diversity and coverage of generated distributions, and close the loop between dataset composition and model performance.

Company info

  • Vinci is building physics AI for hardware design. Our models deliver ultrafast, accurate thermal and mechanical simulation and our platform puts that capability in the hands of every hardware engineer, not just simulation specialists. The quality of our models is bounded by the quality and diversity of the data they're trained on, and that data doesn't exist in the wild. We generate it.
  • General Description
  • You will join the data generation team and build the systems that produce the synthetic geometries, materials, boundary conditions, and simulation configurations used to train and evaluate our physics models.
  • This is a deep technical role at the intersection of computational geometry, physics simulation, and machine learning. The core challenge: write programs that generate families of hardware-like geometries and simulation setups - diverse enough to cover the space our models will see in production, constrained enough that every sample is valid, physically plausible, and useful as training signal.
  • Vinci is building physics AI for hardware design.
  • Our models deliver ultrafast, accurate thermal and mechanical simulation and our platform puts that capability in the hands of every hardware engineer, not just simulation specialists.
  • We generate it.
  • The core challenge: write programs that generate families of hardware-like geometries and simulation setups - diverse enough to cover the space our models will see in production, constrained enough that every sample is valid, physically plausible, and useful as training signal.
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