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Summer Machine Learning Hardware Jobs in Seattle, WA

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

Optimize algorithms for low-latency inference on edge devices (spacecraft hardware). * Collaborate ... Proven experience deploying machine learning models into production. * Strong software engineering ...

If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine ... What You'll Get To Do Machine Learning modeling * Design, train, and deploy state-of-the-art ...

If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine ... What You'll Get To Do Machine Learning modeling * Design, train, and deploy state-of-the-art ...

If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine ... What You'll Get To Do Machine Learning modeling * Design, train, and deploy state-of-the-art ...

Join force with MLEs or firmware or hardware engineers to leverage hardware accelerators and ... in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant ...

Senior Machine Learning Scientist

Seattle, WA · On-site

$104K - $142K/yr

Join force with MLEs or firmware or hardware engineers to leverage hardware accelerators and ... in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant ...

We are seeking a Principal Machine Learning Engineer to accelerate our training of generative ... latest hardware, devising new ways to assess their capabilities, and evolving data and training ...

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Summer Machine Learning Hardware information

See Seattle, WA salary details

$13

$27

$54

How much do summer machine learning hardware jobs pay per hour?

As of Jul 27, 2026, the average hourly pay for summer machine learning hardware in Seattle, WA is $27.99, according to ZipRecruiter salary data. Most workers in this role earn between $19.95 and $31.73 per hour, depending on experience, location, and employer.

What is the difference between Summer Machine Learning Hardware vs Summer Data Scientist?

AspectSummer Machine Learning HardwareSummer Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; knowledge of hardware design and programmingBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and programming
Work EnvironmentHardware labs, R&D centers, tech companies focusing on AI hardwareOffice settings, research labs, tech companies analyzing data and building models
Industry UsageAI hardware development, embedded systems, hardware acceleration for MLData analysis, predictive modeling, AI application development

Summer Machine Learning Hardware roles focus on designing and optimizing hardware for machine learning applications, requiring technical skills in hardware engineering. In contrast, Summer Data Scientist positions involve analyzing data, building models, and deriving insights. Both roles are essential in AI development but differ in their technical focus and work environment.

Machine Learning Engineer

Constellation Space

Seattle, WA • On-site

$120K - $180K/yr

Full-time

Posted 26 days ago


Job description

The Role

We are looking for a Machine Learning Engineer to bridge the gap between AI research and production-grade flight systems. You will optimize, deploy, and scale machine learning models that directly impact Constellation’s orbital systems and ground operations.

Responsibilities

  • Deploy, monitor, and maintain ML models in production environments.

  • Build robust MLOps pipelines for continuous training and integration of models using telemetry data.

  • Optimize algorithms for low-latency inference on edge devices (spacecraft hardware).

  • Collaborate with data scientists and flight software engineers to integrate AI capabilities into core flight systems.

Requirements

  • B.S. or M.S. in Computer Science, Engineering, or equivalent experience.

  • Proven experience deploying machine learning models into production.

  • Strong software engineering skills in Python and C++.

  • Experience with cloud platforms, containerization (Docker), and MLOps tools.

Compensation Range: $120K - $180K