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Scientific Computing Jobs in Seattle, WA (NOW HIRING)

YO AI Labs

GPU Programmer - Remote

Seattle, WA · Remote

$60 - $85/hr

Background in graphics programming, ML acceleration, scientific computing, HPC, or related GPU-focused fields. * Strong understanding of GPU architecture and performan

New

IonQ

Senior HPC Cluster Engineer

Bothell, WA · On-site

$145K - $209K/yr

This role will be a great fit if you enjoy working alongside researchers and want your work to directly accelerate scientific computing. Responsibilities: * Design, deploy, and operate high ...

Socket.dev

Senior HPC Cluster Engineer

Bothell, WA · On-site

$145 - $209.24/hr

This role will be a great fit if you enjoy working alongside researchers and want your work to directly accelerate scientific computing. Responsibilities: * Design, deploy, and operate high ...

Microsoft

Quantum Software Engineer

Redmond, WA · On-site

Overview At Microsoft Quantum, we aim to empower science and scientists to solve the world's biggest problems by realizing advanced computing platforms at the intersection of high-performance ...

University of Washington

Security Analyst

Seattle, WA · On-site

Preferred Qualifications • Experience supporting secure research computing, high-performance computing (HPC), or scientific computing environments. • Experience with security assessments ...

New

Uw

Security Analyst

Seattle, WA · On-site

Preferred Qualifications Experience supporting secure research computing, high-performance computing (HPC), or scientific computing environments. Experience with security assessments, vulnerability ...

New

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Scientific Computing information

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How much do scientific computing jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for scientific computing in Seattle, WA is $35.82, according to ZipRecruiter salary data. Most workers in this role earn between $21.88 and $45.67 per hour, depending on experience, location, and employer.

What is scientific computing?

A Scientific Computing job involves using advanced computational methods, algorithms, and mathematical modeling to solve complex scientific and engineering problems. Professionals in this field develop and optimize software, perform simulations, and analyze large datasets to support research in disciplines like physics, biology, and engineering. They often work with high-performance computing (HPC) systems and programming languages such as Python, C++, or Fortran. These roles are commonly found in academia, government research labs, and industries like aerospace, pharmaceuticals, and finance.

What does someone working in scientific computing do?

Professionals in Scientific Computing typically spend their days developing and optimizing computational models, writing code to analyze large datasets, and running simulations on high-performance computing systems. They often collaborate closely with scientists, researchers, or engineers to interpret results and improve methodologies. Depending on the industry, they may also be responsible for documenting workflows, troubleshooting complex issues, and staying current with technological advances in their field. Daily work often involves problem-solving, technical meetings, and the continuous improvement of algorithms and computational processes.

What are the key skills and qualifications needed to thrive in scientific computing?

To thrive in Scientific Computing, you need a strong background in mathematics, computer science, and scientific principles, often supported by a relevant degree such as physics, engineering, or computational science. Proficiency with programming languages like Python, C++, or MATLAB, experience with high-performance computing (HPC) systems, and familiarity with scientific software and libraries are typically essential. Excellent problem-solving abilities, teamwork, and clear communication skills are important soft skills for this role. These skills enable professionals to develop efficient computational solutions, collaborate effectively across multidisciplinary teams, and drive progress in research and innovation.

What are the most commonly searched types of Scientific Computing jobs in Seattle, WA?

The most popular types of Scientific Computing jobs in Seattle, WA are:

What are popular job titles related to Scientific Computing jobs in Seattle, WA?

For Scientific Computing jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Scientific Computing jobs in Seattle, WA look for?

The top searched job categories for Scientific Computing jobs in Seattle, WA are:

Scientific Computing jobs near you
Infographic showing various Scientific Computing job openings in Seattle, WA as of August 2026, with employment types broken down into 86% Full Time, 10% Part Time, and 4% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $74,510 per year, or $35.8 per hour.

GPU Programmer - Remote

YO AI Labs

Seattle, WA • Remote

$60 - $85/hr

Full-time

Posted 3 days ago

New

Job description

GPU Programmer - Remote

Job Type: Contractor
Location: Remote

Job Overview

We are seeking experienced GPU Programmers / Software Engineers to design and optimize GPU-based tasks for AI and LLM applications. You will apply your expertise in GPU programming, performance optimization, and C++ development to build high-performance solutions.

Key Responsibilities

  • Design, implement, and optimize GPU software using CUDA, WebGPU, or GLSL.

  • Profile and optimize GPU kernels and shaders for performance and efficiency.

  • Develop host-side logic and GPU integrations using C++.

  • Create GPU-focused tasks and solutions for AI/LLM applications.

  • Analyze performance bottlenecks and implement optimization strategies.

Required Qualifications

  • Strong experience with GPU programming, particularly on NVIDIA GPUs.

  • Proficiency in CUDA, WebGPU, or GLSL.

  • Strong C++ programming skills.

  • Background in graphics programming, ML acceleration, scientific computing, HPC, or related GPU-focused fields.

  • Strong understanding of GPU architecture and performan