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Computational Engineering Internship Jobs in Seattle, WA

... Engineering (with computational focus), or related field * Preference for students who have completed 3+ years of coursework by the internship start date * Experience with object-oriented programming ...

... Engineering (with computational focus), or related field * Preference for students who have completed 3+ years of coursework by the internship start date * Experience with object-oriented programming ...

... Engineering (with computational focus), or related field * Preference for students who have completed 3+ years of coursework by the internship start date * Experience with object-oriented programming ...

... Engineering (with computational focus), or related field * Preference for students who have completed 3+ years of coursework by the internship start date * Experience with object-oriented programming ...

... Engineering (with computational focus), or related field * Preference for students who have completed 3+ years of coursework by the internship start date * Experience with object-oriented programming ...

... Engineering (with computational focus), or related field * Preference for students who have completed 3+ years of coursework by the internship start date * Experience with object-oriented programming ...

Basic computational comfort for organizing data, plotting results, and working with standard lab ... internships acceptable, strong hands-on Compensation, Benefits and Position Details Pay Range ...

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Computational Engineering Internship information

See Seattle, WA salary details

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How much do computational engineering internship jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for computational engineering internship in Seattle, WA is $21.98, according to ZipRecruiter salary data. Most workers in this role earn between $18.32 and $23.80 per hour, depending on experience, location, and employer.

What is a computational engineering internship?

A Computational Engineering Internship is a temporary position for students or recent graduates, where they apply their knowledge of computer science, mathematics, and engineering to solve real-world problems using computational methods. Interns typically work on projects involving simulation, modeling, data analysis, or software development in engineering fields. This role provides hands-on experience with industry tools and technologies, and helps interns develop practical skills in areas such as programming, numerical analysis, and algorithm design. Interns may also collaborate with experienced engineers and researchers, contributing to ongoing projects and gaining valuable insights into engineering workflows.

What types of projects does a computational engineering intern typically work on, and how do these projects contribute to their professional development?

Computational Engineering Interns often work on projects involving simulation, modeling, data analysis, or algorithm development to solve real engineering problems. These assignments may include optimizing engineering processes, validating simulation results, or supporting the development of new computational tools. Interns usually collaborate closely with experienced engineers, gaining exposure to industry software and best practices. This hands-on experience not only develops their technical abilities but also helps them build teamwork and communication skills essential for advancing in the field.

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

To thrive as a Computational Engineering Intern, you need a solid background in mathematics, programming (such as Python, MATLAB, or C++), and engineering principles, typically gained through relevant coursework or a degree in engineering, computer science, or a related field. Familiarity with simulation software, numerical analysis tools, and version control systems like Git is often expected. Strong problem-solving abilities, attention to detail, and effective communication skills help you collaborate and contribute to complex engineering projects. These competencies are crucial for efficiently supporting engineering teams and delivering accurate computational analyses in a fast-paced environment.

What is the difference between Computational Engineering Internship vs Mechanical Engineering Internship?

AspectComputational Engineering InternshipMechanical Engineering Internship
Required CredentialsTypically pursuing or holding a degree in computational, software, or engineering disciplinesTypically pursuing or holding a degree in mechanical engineering or related fields
Work EnvironmentFocus on software development, simulations, and modeling in labs or office settingsHands-on hardware, design, and testing in labs, manufacturing, or field environments
Industry UsageUsed in aerospace, automotive, energy, and tech sectors for simulation and analysisCommon in manufacturing, automotive, aerospace, and product design industries

Computational Engineering Internships focus on software, modeling, and simulation tasks, often in tech-driven industries, while Mechanical Engineering Internships involve physical design, testing, and hardware work. Both roles require engineering backgrounds but differ in daily tasks and work environments.

What are the most commonly searched types of Computational Engineering jobs in Seattle, WA?

The most popular types of Computational Engineering jobs in Seattle, WA are:

AI Scientist Intern, Computational Protein Design

Xaira Therapeutics

Seattle, WA

$10K - $15K/mo

Internship

Posted 6 days ago


Job description

About the Role

As an AI Scientist Intern on our Computational Protein Design team, you will work alongside talented scientists and engineers developing generative AI models for protein and antibody therapeutic design. During your internship, you will contribute to advancing state-of-the-art machine learning models for biology, with a focus on impacting protein/antibody design and drug discovery. You will also have the opportunity to collaborate with interdisciplinary experts in biology, drug discovery, and clinical research.

Responsibilities

  • Develop and apply deep learning methods for protein/antibody structure, sequence, or property modeling, under the guidance and mentorship of experienced scientists and engineers
  • Implement and train models on GPUs using PyTorch
  • Contribute to ongoing research projects involving protein structure, sequence, or biophysical/affinity datasets
  • Participate in discussions to help generate innovative ideas for advancing AI methodologies in computational protein design
  • Document findings and communicate progress effectively to peers and mentors

Qualifications

  • Currently pursuing a MS or PhD in Computer Science, Machine Learning, or a related technical field, with strong publication record
  • Hands-on experience with PyTorch and training/inference of AI models on GPUs
  • Strong interest in AI innovation and its applications to interdisciplinary fields such as biology and chemistry
  • Extensive hands-on experience with deep learning methods and frameworks
  • Ability to work collaboratively in a team environment and learn from experienced mentors
  • A scientifically curious mindset with a passion for exploring new challenges
  • Experience with large-scale distributed training and inference is a plus
  • Exposure to molecular structure or biological sequence data or computational biology/bioinformatics is a plus, but not required
  • Prior research experience demonstrated through publications and/or significant open source code authorship
  • Interest in contributing to open-source deep learning libraries and frameworks is a plus

Internship Duration
3 months
The expected monthly compensation range is $10,000-$15,000, depending on experience and qualifications. We are open to higher compensation for candidates with exceptional experience or impact. This internship is designed to provide a unique learning experience, offering hands-on exposure to the intersection of AI and computational protein design while allowing you to contribute meaningfully to real-world projects.