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Cuda Openmp Jobs (NOW HIRING)

OptechUs

Automotive Controls Algorithm Engineer

Warren, MI

$78K - $101K/yr

... CUDA, OpenMP, etc.) - Experience in image/signal processing algorithm development and implementation - Demonstrated experience in automotive embedded system development. - Working knowledge of radar ...

Nvidia

Senior System Software Engineer, ML and Vector Search

OR · On-site +1

$122K - $161K/yr

You care deeply about robust, readable, high-performance code Familiar with at least one parallel programming or concurrency framework, such as CUDA, OpenMP, OpenACC, Java concurrency, pthreads, etc ...

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Cuda Openmp information

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$206K

How much do cuda openmp jobs pay per year?

As of Sep 14, 2026, the average yearly pay for cuda openmp in the United States is $200,510.00, according to ZipRecruiter salary data. Most workers in this role earn between $205,000.00 and $205,000.00 per year, depending on experience, location, and employer.

What is the difference between Cuda Openmp vs C++ Developer?

AspectCuda OpenmpC++ Developer
Required CredentialsKnowledge of GPU programming, CUDA, OpenMP, parallel computingProficiency in C++, algorithms, software development
Work EnvironmentHigh-performance computing, parallel processing environmentsSoftware development across various industries
Industry UsageResearch, scientific computing, AI, HPCSoftware engineering, application development, system programming

While Cuda Openmp focuses on parallel programming for GPU and CPU acceleration, C++ Developers create software applications across multiple domains. Both roles require strong programming skills, but Cuda Openmp specialists emphasize parallel computing techniques, whereas C++ Developers focus on software design and implementation.

What other helpful pages are available for Cuda Openmp?

Other pages related to Cuda Openmp:

Infographic showing various Cuda Openmp job openings in the United States as of September 2026, with employment types broken down into 98% Full Time, 1% Part Time, and 1% Contract. Highlights an 77% Physical, 5% Hybrid, and 18% Remote job distribution, with an average salary of $200,510 per year, or $96.4 per hour.

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

Mountain View, CA • On-site

Saransh Inc
IT Services • 51 - 200 employees
Learn more about Saransh Incexternal

Contractor

Re-posted 27 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