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Voxel Maps Jobs (NOW HIRING)

General Atomics

Engineer III

Poway, CA · On-site

$81K - $141K/yr

Spatiotemporal voxel grids / occupancy & belief fields * Confidence, decay, and provenance tracking ... Spatiotemporal mapping or occupancy grid systems * STAP/DPCA basics or RF signal chain awareness

All JobsVoxel Maps Jobs

Voxel Maps information

What are voxel maps?

Voxel maps are three-dimensional grids composed of tiny cubes, known as voxels, that represent data points in 3D space. Unlike traditional 2D maps or pixel-based images, voxel maps allow for the visualization and analysis of volumetric data, making them useful in fields like medical imaging, 3D modeling, and geospatial analysis. These maps help professionals interpret complex structures and patterns within a given volume, offering detailed insights that aren't possible with flat, two-dimensional representations.

What skills and qualifications are needed to work with voxel maps?

To thrive as a Voxel Map Specialist, you need strong spatial reasoning, 3D modeling experience, and a background in GIS, computer science, or a related field. Proficiency with voxel-based mapping software, geographic information systems (GIS), and programming languages like Python or C++ is typically required. Attention to detail, problem-solving skills, and effective communication help in accurately interpreting data and collaborating with interdisciplinary teams. These skills are crucial for creating precise, usable 3D representations that inform decision-making in fields such as urban planning, gaming, and autonomous navigation.

What challenges do professionals working on voxel maps face, and how do they address them?

Professionals working on Voxel Maps often encounter challenges related to managing large datasets, ensuring real-time rendering performance, and maintaining spatial accuracy. Handling the computational demands of voxel-based representations requires strong optimization skills and familiarity with parallel processing. Collaboration with teams specializing in data acquisition, graphics programming, and user experience is common to ensure the maps are both accurate and user-friendly. Staying updated with the latest advancements in 3D mapping technologies and techniques is also essential for continuous improvement.

What is the difference between Voxel Maps vs 3D Map Developers?

AspectVoxel Maps3D Map Developers
Required CredentialsGIS certifications, 3D modeling skillsGIS certifications, 3D modeling skills
Work EnvironmentGIS firms, gaming, simulationGIS firms, urban planning, gaming
Industry UsageMapping, gaming, virtual realityMapping, urban planning, gaming

Both Voxel Maps and 3D Map Developers require similar skills and certifications, often working within GIS, gaming, or simulation industries. Voxel Maps focus on volumetric data representation, while 3D Map Developers create detailed 3D environments. Their roles overlap in 3D visualization, but Voxel Maps are more specialized in volumetric data, whereas 3D Map Developers emphasize environment creation and interactivity.

More about Voxel Maps jobs

What are the most commonly searched types of Voxel Maps jobs?

The most popular types of Voxel Maps jobs are:

What job categories do people searching Voxel Maps jobs look for?

The top searched job categories for Voxel Maps jobs are:

Voxel Maps jobs near you
Infographic showing various Voxel Maps job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Lead Data Scientist (Scientific Software Engineer / Computational Scientist) - Only W2

Saransh Inc

Mountain View, CA • On-site

Contractor

Re-posted 8 days ago

Job description

Role: Lead Data Scientist (Scientific Software Engineer / Computational Scientist)
Location: Mountain View, CA (Hybrid – 3 days a week onsite)
Job Type: W2 Contract
 
 
Note: Only Visa Independent candidates are required (No C2C or Third-party candidates)
 
 
Experience Level: Lead
 
Main Skills:
  • Python (NumPy/SciPy/CuPy)
  • C++
  • PyTorch
  • 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:
  1. 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
  2. Generative ML Engineering — Architect and train models (GANs, Diffusion) for high-resolution 3D spatial data using PyTorch
    • 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 (NumPy/SciPy/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/GitHub demonstrating procedural world-building, physics engines, or scientific simulators