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Remote Computational Engineering Jobs in Austin, TX

Cornelis Networks

Senior Software Engineer - AI Middleware

Austin, TX · On-site +1

$121K - $160K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... computational challenges with our next-generation networking solutions. We are a fast-growing ... Location:This is a remote position for employees residing within the United States. We offer a ...

NextSilicon

HPC Field Applications Engineer

Austin, TX · On-site +1

Bachelor of Science in an engineering discipline (computer science, mathematics, natural sciences ... computational fluid dynamics, molecular dynamics, high-energy or astro physics, quantum chemistry ...

Wsgr

Innovations and AI Solutions Engineer

Austin, TX · On-site +1

This position is available as a hybrid or remote work schedule. Essential Duties, Responsibilities ... Leverage statistics and computational techniques in problem solving. * Be familiar with common NLP ...

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All JobsComputational Engineering JobsRemote Computational Engineering JobsRemote Computational Engineering Jobs in Austin, TX

Remote Computational Engineering information

See Austin, TX salary details

$48.1K

$120.4K

$136.3K

How much do remote computational engineering jobs pay per year?

As of Aug 14, 2026, the average yearly pay for remote computational engineering in Austin, TX is $120,447.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,500.00 and $130,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a remote computational engineer, and why are they important?

To thrive as a Remote Computational Engineer, you need strong analytical and mathematical abilities, proficiency in computational modeling, and a degree in engineering, mathematics, or a related field. Familiarity with programming languages (such as Python, MATLAB, or C++), high-performance computing systems, and relevant simulation software is typically required. Excellent problem-solving, self-motivation, and clear communication skills help you collaborate effectively in a remote environment. These skills ensure that you can develop accurate models, contribute to complex projects, and maintain productivity while working independently.

How does a remote computational engineer typically collaborate with team members on complex projects?

Remote computational engineers often use collaborative software tools, such as version control systems, cloud-based simulation platforms, and video conferencing, to stay connected with their teams. They regularly participate in virtual meetings, share project updates, and review code or modeling results together. Despite working remotely, strong communication skills are essential to coordinate with multidisciplinary teams, address technical challenges, and ensure alignment on project goals and deadlines.

What is remote computational engineering?

Remote computational engineering involves using computer-based simulations and modeling tools to solve engineering problems from a remote location, rather than working onsite. Professionals in this field apply advanced mathematics, physics, and programming to design, analyze, and optimize systems or products. They often collaborate with teams virtually and use software to perform tasks such as finite element analysis (FEA), computational fluid dynamics (CFD), or algorithm development. This role enables flexibility in work location while contributing to innovative engineering projects across various industries.

What is the difference between Remote Computational Engineering vs Remote Data Scientist?

AspectRemote Computational EngineeringRemote Data Scientist
Required CredentialsBachelor's or higher in engineering, computer science, or related fields; programming skillsBachelor's or higher in statistics, computer science, or related fields; programming and statistical skills
Work EnvironmentCollaborative engineering teams, simulation labs, software developmentData analysis teams, research environments, analytics platforms
Industry UsageEngineering firms, tech companies, manufacturing
Common Search IntentComparing roles in engineering and technical development

Remote Computational Engineering and Remote Data Scientist roles share a focus on programming and analytical skills, often requiring similar educational backgrounds. However, computational engineers typically work on simulations, modeling, and engineering solutions, while data scientists focus on analyzing data to derive insights. Both roles are prevalent in tech-driven industries and often involve remote collaboration, but their core functions differ in application and industry focus.

What are the most commonly searched types of Computational Engineering jobs in Austin, TX?

The most popular types of Computational Engineering jobs in Austin, TX are:

What are popular job titles related to Remote Computational Engineering jobs in Austin, TX?

For Remote Computational Engineering jobs in Austin, TX, the most frequently searched job titles are:

What job categories do people searching Remote Computational Engineering jobs in Austin, TX look for?

The top searched job categories for Remote Computational Engineering jobs in Austin, TX are:

What cities near Austin, TX are hiring for Remote Computational Engineering jobs?

Cities near Austin, TX with the most Remote Computational Engineering job openings:

Remote Computational Engineering jobs near you
Infographic showing various Remote Computational Engineering job openings in Austin, TX as of August 2026, with employment types broken down into 77% Full Time, 7% Part Time, and 16% Contract. Highlights an 100% Remote job distribution, with an average salary of $120,447 per year, or $57.9 per hour.

R&D Data Scientist: Mathematical Modeling and Optimization

Liftlab Analytics, Inc.

Austin, TX • On-site, Remote

Full-time

Re-posted 25 days ago

Job description

(Fully-remote US position)
About LiftLab
Liftlab is the leading provider of science-driven software to optimize marketing spend and predict revenue for optimal spend levels. We call this the Science of Marketing Effectiveness. Our platform combines economic modeling with specialized media experimentation so brands and agencies can clearly see the tradeoffs of growth and profitability. With decades of experience in marketing analytics and data science, our team of industry experts and thought leaders is proud to enable leading and emerging brands such as Cinemark, Express, Hanna Anderson, Lulu & Georgia, Pandora, Sephora, Skims, Tory Burch, Thrive, and Vionic, with our cutting-edge solutions and strategic guidance.
Job responsibilities
  • Develop new algorithm-based features of LiftLab's marketing measurement and optimization platform
  • Performs diagnostics and root-cause analysis and provide fixes
  • Works with Data Science and Engineering to implement these features into LiftLabs product and workflow
Course work/experience:
  • Data manipulation
    • SQL
    • Operating on big datasets in Python
    • Data visualization
  • Mathematical optimization
    • Linear optimization concepts
    • Nonlinear continuous optimization
    • Linear algebra
  • Mathematical modeling
    • Using parametrized systems of equations to represent real-world systems
  • Statistics
    • Multivariate regression
    • Clear understanding of Maximum Likelihood estimation and computational methods to find MLE parameters
    • Bayesian concepts
    • Hypotheses testing
Education requirements
Graduate degree in Applied Mathematics, Scientific Computing, Operations Research or related field. We will consider holders of Bachelor degrees with relevant experience
Skills/Aptitude
  • Engineering and detective mindset
    • Both to diagnose data and existing algorithms and to develop new analytics functionality
  • Pragmatic approach to real-world problems
  • Focus on problem solving over applying specific models
  • Willingness to make approximations and assumptions rather than find "the" optimal solution
  • Ability to combine multiple techniques and models to solve end-to end-problems
  • Communication and collaboration skill
  • Ability to convert non-technical requests into project specifications

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