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Hourly Embedded Machine Learning Jobs in Seattle, WA

Axon

Senior Software Embedded Engineer

Seattle, WA · On-site

$141K - $225K/yr

Collaborate with engineers across embedded software, cloud, and machine learning to deliver new streaming capabilities. * Help shape the architecture and technical direction of Axon's native ...

Geico

Senior Machine Learning Engineer

Seattle, WA · On-site

$115K - $230K/yr

Multiple factors are taken into consideration to arrive at the final hourly rate/ annual salary to be offered to the selected candidate. Factors include, but are not limited to, the scope and ...

Geico

Staff Machine Learning Engineer

Seattle, WA · On-site

$130K - $260K/yr

Multiple factors are taken into consideration to arrive at the final hourly rate/ annual salary to be offered to the selected candidate. Factors include, but are not limited to, the scope and ...

Amazon

Sr. SDE, EC2 Nitro Networking

Seattle, WA · On-site

$139K - $183K/yr

... Machine Learning workloads across HPC and Accelerated Platforms in EC2 Nitro. We are seeking a Sr. Software Engineer with experience in Dataplane development, System Software/Embedded software, Cloud ...

Amazon

Software Engineer, EC2 Nitro

Seattle, WA · On-site

... Machine Learning workloads across HPC and Accelerated Platforms in EC2 Nitro. We are seeking a Software Engineer with experience in Dataplane development, System Software/Embedded software, Cloud ...

Amazon

Software Engineer, EC2 Nitro

Seattle, WA · On-site

... Machine Learning workloads across HPC and Accelerated Platforms in EC2 Nitro. We are seeking a Software Engineer with experience in Dataplane development, System Software/Embedded software, Cloud ...

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All JobsHourly Embedded Machine Learning JobsHourly Embedded Machine Learning Jobs in Seattle, WA

Hourly Embedded Machine Learning information

See Seattle, WA salary details

$79.7K

$174.6K

$198K

How much do hourly embedded machine learning jobs pay per year?

As of Aug 22, 2026, the average yearly pay for hourly embedded machine learning in Seattle, WA is $174,554.00, according to ZipRecruiter salary data. Most workers in this role earn between $149,600.00 and $196,900.00 per year, depending on experience, location, and employer.

What is an hourly embedded machine learning engineer?

An Hourly Embedded Machine Learning engineer is a professional who specializes in developing and deploying machine learning models on embedded systems, such as microcontrollers, IoT devices, or edge devices, and is compensated on an hourly basis rather than a salaried or project-based arrangement. These engineers work to optimize algorithms so they can run efficiently on devices with limited computing power, memory, and energy resources. Their responsibilities often include model selection, quantization, optimization, and integration of machine learning pipelines into hardware. Hiring on an hourly basis allows for flexibility in project scope and duration, making it ideal for companies with specific, time-limited needs. They often collaborate with hardware engineers, data scientists, and software developers to create intelligent embedded solutions.

How does an hourly embedded machine learning professional typically collaborate with hardware and software teams during a project?

As an Hourly Embedded Machine Learning professional, you will often work closely with both hardware and software engineering teams to ensure that machine learning models are efficiently integrated into embedded systems. This typically involves frequent communication to align on hardware constraints, such as memory and processing power, and to optimize algorithms for real-time performance. You may also participate in joint debugging sessions and code reviews to address integration issues and streamline deployment. Collaboration is key, as successful projects depend on the seamless interaction between machine learning solutions and the embedded hardware platform.

What are the key skills and qualifications needed to thrive as an hourly embedded machine learning engineer, and why are they important?

To thrive as an Hourly Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer engineering or a related field. Familiarity with tools such as TensorFlow Lite, embedded Linux, microcontroller development environments, and model optimization frameworks is typically required. Strong problem-solving skills, adaptability, and effective communication help you address complex technical challenges and collaborate with cross-functional teams. These skills are crucial for designing efficient, real-time ML solutions that operate reliably on resource-constrained embedded devices.

What is the difference between Hourly Embedded Machine Learning vs Hourly Data Scientist?

AspectHourly Embedded Machine LearningHourly Data Scientist
CredentialsKnowledge of embedded systems, programming, ML algorithmsDegree in Data Science, Statistics, or related field
Work EnvironmentEmbedded hardware, IoT devices, real-time systemsData analysis, modeling, visualization in office or cloud
Industry UsageConsumer electronics, automotive, IoT devicesFinance, healthcare, marketing, research

Hourly Embedded Machine Learning specialists focus on integrating ML models into embedded systems and hardware, often working with IoT devices and real-time constraints. In contrast, Hourly Data Scientists analyze large datasets to develop predictive models primarily in cloud or office environments. While both roles require programming skills, embedded ML emphasizes hardware integration, whereas data science centers on data analysis and visualization.

What are popular job titles related to Hourly Embedded Machine Learning jobs in Seattle, WA?

For Hourly Embedded Machine Learning jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Hourly Embedded Machine Learning jobs in Seattle, WA look for?

The top searched job categories for Hourly Embedded Machine Learning jobs in Seattle, WA are:

Hourly Embedded Machine Learning jobs near you
Infographic showing various Hourly Embedded Machine Learning job openings in Seattle, WA as of June 2026, with employment types broken down into 77% Full Time, 11% Part Time, 4% Temporary, 4% Contract, and 4% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $174,554 per year, or $83.9 per hour.

Embedded Software Dev Engineer, AWS Hardware Engineering

Amazon

Seattle, WA • On-site

$149K - $196K/yr

Full-time

Re-posted 4 days ago

Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 7,105 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers

Job description

Join AWS Hardware Engineering to design the servers powering the world's leading cloud platform and AI/ML infrastructure. We're seeking an exceptional Embedded Software Engineer for our team to accelerate critical firmware initiatives across millions of servers worldwide.
We are seeking an exceptional Embedded Software Engineer to join our BMC (Baseboard Management Controller) team. In this role, you will accelerate critical firmware migration initiatives across our massive server fleet while delivering security and operationally critical features that directly impact AWS infrastructure reliability

Your work will power the backbone of AWS compute infrastructure, including the servers that enable AI/ML workloads for customers worldwide.
The ideal candidate will be an innovative self-starter with deep expertise in firmware and embedded systems. You will gain comprehensive understanding of our server firmware stack and analyze it in both current and future contexts. Using your systems knowledge, you will architect solutions to complex multi-factor problems, including firmware deployment strategies that minimize customer impact and optimize operational efficiency across millions of servers supporting diverse workloads from traditional compute to advanced machine learning applications.
You will collaborate with engineers across AWS and external partners, leading development efforts that span architecture, hardware validation, and software services teams

Your work will directly contribute to critical initiatives that enhance our infrastructure security, reliability, and operational excellence-ensuring the foundation for tomorrow's AI/ML innovations remains robust and scalable.
AWS Engineers are shaping the way people use computers and designing the future of cloud computing technology - come help us make history!
Key job responsibilities
Design and develop firmware solutions for AWS servers, contributing to server designs that power millions of customer workloads.
Lead the complete development lifecycle from initial conception through production deployment, ensuring robust and scalable firmware implementations across our massive server fleet.
Architect and implement firmware deployment strategies that minimize customer impact while maintaining the highest standards of security and operational excellence.
Collaborate closely with cross-functional teams including hardware engineers, validation teams, software services to optimize functionality and performance.
Explore and evaluate emerging technologies and their potential impact on AWS infrastructure, making recommendations for adoption and integration into our firmware stack.
Drive technical solutions for problems, balancing security requirements, operational efficiency, and system reliability.
Tailor firmware solutions specifically for the AWS environment, ensuring seamless integration with our unique infrastructure requirements and operational workflows.
Mentor team members and contribute to the continuous improvement of development processes, tools, and best practices.
A day in the life
Most mornings, you'll dive into code-whether that's developing new security features, optimizing firmware deployment strategies, or debugging a tricky issue that's affecting a subset of servers.
You'll collaborate a lot. Maybe it's a quick sync with platform teams about an upcoming deployment, or a deeper technical discussion with hardware engineers about a new server design. You might work with internal customers to understand their requirements.
Some days you'll be architecting solutions to complex problems

Other days you might be mentoring a teammate through a code review or exploring a new technology that could improve our firmware stack.

What Amazon employees say

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About Amazon

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Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate, computer and electronic product manufacturing and software development

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US

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