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Remote Openfoam Jobs in Point Venture, TX (NOW HIRING)

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Remote Openfoam information

See Point Venture, TX salary details

$27

$32

$35

How much do remote openfoam jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for remote openfoam in Point Venture, TX is $32.20, according to ZipRecruiter salary data. Most workers in this role earn between $30.29 and $34.09 per hour, depending on experience, location, and employer.

What is the difference between Remote Openfoam vs Remote CFD Engineer?

AspectRemote OpenfoamRemote CFD Engineer
Required credentialsKnowledge of OpenFOAM, engineering backgroundCFD software proficiency, engineering degree
Work environmentRemote, computational modelingRemote, simulation and analysis
Industry usageResearch, academia, engineering firmsEngineering, aerospace, automotive

Remote Openfoam focuses on using the OpenFOAM software for computational fluid dynamics tasks, often requiring specific software knowledge. Remote CFD Engineer covers a broader range of CFD tools and applications, with similar credentials. Both roles are remote and industry-relevant, but Remote Openfoam is more specialized in OpenFOAM software, while Remote CFD Engineer may involve multiple CFD platforms.

What is a remote OpenFOAM?

A Remote OpenFOAM job refers to a position in which professionals use OpenFOAM, an open-source computational fluid dynamics (CFD) software, to perform simulations and analyses from a remote location rather than on-site. These roles typically involve tasks such as setting up CFD models, running simulations, post-processing results, and collaborating with teams or clients online. Remote OpenFOAM jobs are common in industries like engineering, automotive, aerospace, and research, offering flexibility in location while working on complex fluid dynamics problems. Candidates for these roles usually require strong computational skills, experience with OpenFOAM, and the ability to communicate effectively in a virtual environment.

What are some common challenges faced by remote OpenFOAM engineers, and how can they be effectively managed?

Remote OpenFOAM engineers often encounter challenges related to collaboration and accessing high-performance computing resources. Since computational fluid dynamics projects can require significant computational power, it's important to ensure you have reliable remote access to servers or cloud-based HPC environments. Effective communication with team members, regular updates, and clear documentation help overcome the barriers of working remotely. Utilizing collaborative tools and version control systems also streamlines teamwork and project management, ensuring your contributions integrate smoothly with the overall workflow.

What are the key skills and qualifications needed to thrive as a remote OpenFOAM engineer?

To thrive as a Remote OpenFOAM Engineer, you need a strong background in computational fluid dynamics (CFD), programming (e.g., C++), and a relevant engineering or science degree. Proficiency with OpenFOAM software, Linux operating systems, and version control tools like Git is typically required. Strong problem-solving abilities, effective communication, and self-motivation are vital soft skills for remote collaboration and project management. These skills ensure accurate simulations, efficient workflow, and successful teamwork in distributed engineering environments.
What are the most commonly searched types of Openfoam jobs in Point Venture, TX? The most popular types of Openfoam jobs in Point Venture, TX are:
Remote Openfoam jobs near you

Physicist with Python Proficiency - AI Trainer

Kake Group

Austin, TX • Remote

$51.50 - $71/hr

Contractor

Re-posted 21 days ago

Job description

We're building a talent pool of Physics Experts with Python proficiency to contribute to project-based AI development initiatives, focused on evaluating and enhancing frontier AI models.

Designed for physics professionals who enjoy deep technical problem-solving, this pipeline role is for those looking to apply their simulation expertise to evaluate and push the boundaries of frontier AI models, relying on domain-specific simulation tools, such as FEniCS, OpenFOAM, Meep, REBOUND, or CAMB, with verifiable, code-graded answers run inside isolated Linux environments.

Key Responsibilities

  • Identify an appropriate physics simulation package and build problems whose solution genuinely hinges on that tool's core capabilities, whether PDE solvers, integrators, or Monte Carlo kernels.
  • Develop full Python solutions for each problem, providing all necessary input files, boundary conditions, and domain or initial condition definitions.
  • Establish the correct numerical output and define how close the AI model needs to get, using tolerance values appropriate to the physical context.
  • Run the problem against the AI model across multiple parallel attempts, analyzing where it succeeds or falls short, and adjusting difficulty until the pass rate falls between 10% and 30%.
  • Tune solver parameters, field configurations, and initial conditions iteratively, building an understanding of how the model navigates complex simulation environments.
  • Hand off completed tasks to a senior reviewer in your subfield and refine based on their feedback before final submission.

Core Requirements

  • Academic background in Physics, Theoretical, Experimental, or Computational, or an equivalent field.
  • At least 2 years of hands-on experience in physics research, applied work, or teaching.
  • Solid Python skills, applied to writing and validating computational solutions.
  • Capacity to build problems that cannot be solved without specialized simulation software.
  • Excellent written and verbal communication skills in English.
  • Ability to work independently in a remote, fast-paced environment.

Nice-to-Have

  • Working knowledge of one or more domain-specific simulation tools, including but not limited to: FEniCS/DOLFINx, OpenFOAM, Meep, MPB, openEMS, Geant4, PYTHIA8, ROOT/PyROOT, WarpX, REBOUND, MESA, CAMB, CLASS, or Bilby, or a demonstrated ability to get up to speed independently.
  • Prior exposure to how frontier AI models approach complex simulation tasks.
  • Knowledge spanning more than one physics domain, such as fluid dynamics, electromagnetism, gravitation, or cosmology.
  • Familiarity with containerized or sandboxed Linux execution environments.

Please Note: Due to the high volume of applications, only shortlisted candidates will be contacted.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.