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Lead Data Scientist; Scientific Software Engineer​/Computational Scientist – W2

Job in Mountain View, Santa Clara County, California, 94039, USA
Listing for: Info Dinamica Inc
Part Time position
Listed on 2026-02-28
Job specializations:
  • Engineering
    AI Engineer, Computer Science, Artificial Intelligence, Mathematics
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Lead Data Scientist (Scientific Software Engineer / Computational Scientist) – Only W2

Role:
Lead Data Scientist (Scientific Software Engineer / Computational Scientist)

Location:
Mountain View, CA (Hybrid 3 days a week onsite)

Job Type: W2 Contract

Experience Level: Lead

Main

Skills:

  • Python (Num Py/Sci Py/CuPy)
  • C
  • Py Torch
  • Geostatistics
  • 3D Mathematics
  • CUDA/OpenMP
  • AI-assisted coding

Short Overview:

  • Scientific Software Engineer or Computational Scientist with a niche background in scientific simulation, procedural generation, or computational physics.
  • This is an implementation-heavy role requiring a developer who can translate complex mathematical logic and generative ML models into performant code to solve high-dimensional geometric problems.
Simulation & Generative Modeling

Seeking a deep expertise in scientific computing, procedural generation, or computational physics to build the core algorithms for our 3D subsurface modeling engine.

The Role

This is an implementation-heavy position bridging procedural physics and generative ML.

What We’re Looking For Core Competencies
  • Procedural Generation
    :
    Terrain synthesis, voxel engines, noise-driven systems
  • Scientific Computing
    : CFD, FEA, multi-physics solvers
  • Computational Geometry
    : 3D mesh processing, volumetric data structures, spatial partitioning
Key Responsibilities
  • Algorithmic Implementation – Design memory-efficient algorithms for massive 3D voxel arrays and sparse data structures; implement deterministic and stochastic geometric rules
    • Example:
      Build C/Python kernels using 3D Perlin/Simplex noise and vector fields to simulate braided river systems
    • Example:
      Implement Boolean CSG algorithms for volumetric injections of igneous bodies
  • Generative ML Engineering – Architect and train models (GANs, Diffusion) for high-resolution 3D spatial data using Py Torch
    • Example:
      Generate realistic fracture networks via 3D generative models
    • Example:
      Apply neural style transfer to map sedimentary textures onto volumetric frameworks
    Required Technical Skills
    • Languages
      :
      Expert Python (Num Py/Sci Py/CuPy); proficient C for performance kernels
    • Mathematics
      :
      Linear algebra, vector calculus, coordinate transformations
    • ML Frameworks
      :
      PyTorch (generative AI, computer vision)
    • Performance
      : CUDA/OpenMP; parallel computing experience
    • Workflow
      : AI-assisted coding for rapid prototyping and testing
    Domain Knowledge Mathematical maturity in
    • Structural modeling
    • Sedimentology
    • Tectonics
    • Geostatistics
    Ideal Background
    • MS/PhD in Computer Science, Applied Mathematics, Computational Physics, or equivalent
    • Portfolio/Git Hub demonstrating procedural world-building, physics engines, or scientific simulators
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