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

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

On site

Mountain view, United states

Senior

Freelance

19-02-2026

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Skills

Python GitHub PyTorch Computer Vision Numpy C++ Mathematics

Job Specifications

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.

Core Competencies

What We're Looking For:

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 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

About the Company

We provide recruitment, consulting and IT services for our clients, which focus on maximizing their revenue generation, enhancing business productivity and improving cost management. Know more