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Cuda Physics Jobs (NOW HIRING)

Genesis AI

Kernels are written once, and Quadrants, our in-house JIT compiler, lowers them to CUDA, AMD ROCm ... No physics off limits: water, human animation, air flow, gravel, tendons, even body organs.

Voltai

Computational Scientist

Palo Alto, CA · On-site

NCCL, CUDA-aware MPI, NVLink topologies * Published work in neural operators, physics-informed ML, or scientific HPC * IC design domain knowledge: device physics, semiconductor materials, layout data ...

Sciotex

Experience with C++, CUDA, GPU programming, real-time systems, edge devices, or embedded deployment. * Familiarity with inverse problems, physics-informed ML, Bayesian methods, uncertainty ...

Voltai, Inc

Computational Scientist

Palo Alto, CA · On-site

NCCL, CUDA-aware MPI, NVLink topologies * Published work in neural operators, physics-informed ML, or scientific HPC * IC design domain knowledge: device physics, semiconductor materials, layout data ...

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Cuda Physics information

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$11K

$61.2K

$94.5K

How much do cuda physics jobs pay per year?

As of Sep 10, 2026, the average yearly pay for cuda physics in the United States is $61,160.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,000.00 and $64,500.00 per year, depending on experience, location, and employer.

What is the difference between Cuda Physics vs Cuda Developer?

AspectCuda PhysicsCuda Developer
Required CredentialsPhysics degree, knowledge of CUDA, GPU computingComputer science/engineering degree, programming skills, CUDA expertise
Work EnvironmentResearch labs, scientific institutions, academiaTech companies, software development firms, industry
Industry UsageScientific simulations, research projectsSoftware development, performance optimization

While both roles require CUDA knowledge, Cuda Physics focuses on applying GPU computing to physics research, whereas Cuda Developer emphasizes software development and optimization across various applications. The roles overlap in CUDA expertise but differ in their primary focus and work environment.

Infographic showing various Cuda Physics job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, 1% Contract, and 1% Nights. Highlights an 76% Physical, 2% Hybrid, and 22% Remote job distribution, with an average salary of $61,160 per year, or $29.4 per hour.

Physics Applications - Researcher

Palo Alto, CA • On-site

Vinci AI
See more jobs at Vinci AIexternal

$190K - $260K/yr

Full-time

Re-posted yesterday

Key responsibilities

  • Leverage the Vinci framework to work on novel physics applications and experiment with temporal propagation schemas.

  • Use data generation infrastructure to create and verify training and validation samples, and iterate with customers to improve features.

  • Collaborate with physicists, AI researchers, software engineers, and computational geometry experts to develop and harden prototypes for customer use.

Job description

The Mission
At Vinci, we are building the operator intelligence infrastructure that modern hardware programs rely on daily. We have already proven that a single foundation model works out of the box across physics on realistic production workloads.
  • Trained on PetaBytes of structured physics data
  • Running billion-voxel inference in production
  • Tier-1 semiconductor and hardware customers
  • Operating across multiple physical scales and operator regimes

We are scaling deployment at industrial magnitude:
  • Increase simulation throughput by two orders of magnitude
  • Expand simulation capabilities to maximize utility and domain coverage
  • Support global, multi-entity deployment across Tier-1 ecosystems
  • Our ambition is to become the default operator intelligence layer that hardware companies run on

Solving Across Space and Time
Our proven unified model architecture allows users to rapidly obtain steady state solutions of various partial differential equations. We are expanding this capability into the transient domain, modeling interactions, deformation and dynamics. These are promising applications where Vinci's approach can not only reduce the compute load but also achieve greater accuracy.
What You Will Do
Your north star will be production and delivering value to our customers.
In this role you will leverage the Vinci framework to work on a variety of novel applications. Experiment with temporal propagation schemas, both in the classical and learned sense. You will use pre-existing data generation infrastructure to generate and curate training and verification samples. You will take modest iterative steps to prove out new utility and iterate hand in hand with customers to harden features.
You will work with Physicists, AI researchers, Software Engineers and Computational Geometry experts. You will work with a team to carry early prototypes through iteration and hardening all the way to customer use.
What We're Looking For
Qualifications;
  • Have published work leveraging or building a simulation practice.
    • MS/MSc with 4+ years experience or
    • PhD with 2+ years experience
  • 2+ years using or building physics simulators
    • FEM, FEA, Molecular Dynamics, FDTD
  • Applied machine learning approaches
    • Computer Vision, GraphNN, Transformer Architectures
  • Working knowledge of modern ML basics
    • back prop, loss functions, generators, embeddings, transformer models
  • Experience with some modern ML practices
    • PyTorch, Numpy, Cuda
    • Training & Evaluation practices
  • Have contributed to a production data processing system.

We are very excited to talk with you if you have
  • Applied ML to the problem of
  • Meshing geometry
  • Accelerating FEM or DFT simulations
  • Experience going from early stage prototype moving to a production environment at a Startup or National Lab
  • Have leveraged simulation for design or data generation purposes.

Engineering Expectations
  • Software engineering fundamentals
    • Comfortable meeting software design standards to get code into a production environment.
  • Capable of leveraging pre-existing infrastructure and "closing the gap" on occasion
  • Strong CI, regression testing, and validation discipline
  • Comfort evolving core model infrastructure

Why Vinci
Join a rare early-stage startup that has successfully moved a foundational product from research to real-world, production environments, already serving Tier-1 semiconductor and hardware customers.
Our Mission & Impact
Vinci is building the operator intelligence infrastructure that modern hardware programs rely on daily. We are scaling our solution to accelerate design validation from hours to seconds. You will contribute to expanding our unified model architecture, which currently runs billion-voxel inference, into the transient domain-a key frontier in modeling interactions, deformation, and dynamics. Our ambition is to become the default operator intelligence layer for hardware companies.
Growth & Opportunity
This is a unique opportunity for technical and professional growth, as you will define a foundational abstraction layer early in the company's trajectory. The team is small, friendly, and accessible. You will be empowered to "own and architect large pieces of the system" alongside a team of Physicists, AI researchers, Software Engineers, and Computational Geometry experts. This includes greenfield opportunities to expand Vinci's core capabilities.
Leadership
You will work with spectacular technical leaders like CTO Sarah Osentoski and CEO Hardik Kabaria, whose vision is to greatly accelerate physics simulations with ML while retaining solver grade accuracy.

Apply