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Embedded Machine Learning Engineer Jobs in Seattle, WA

Machine Learning Engineer, Growth

Seattle, WA ยท On-site

$150K - $180K/yr

Who you are Metropolis is seeking a Machine Learning Engineer to develop and expand our revenue forecasting and dynamic pricing systems. This position is part of the machine learning team within the ...

Senior Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at ...

Senior Machine Learning Engineer

Seattle, WA ยท On-site

$160K - $250K/yr

Senior Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at ...

Staff Machine Learning Engineer

Seattle, WA ยท On-site

$200K - $300K/yr

Staff Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at ...

About the Role We are looking for a motivated, entry-level Machine Learning Engineer to help build, train, and deploy ML models that power our Marketing AI and AI Sales Agent products. This role is ...

Staff Machine Learning Engineer

Seattle, WA ยท On-site

$200K - $300K/yr

Staff Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at ...

Machine Learning Engineer, Growth

Seattle, WA ยท On-site

$150K - $180K/yr

Who you are Metropolis is seeking a Machine Learning Engineer to develop and expand our revenue forecasting and dynamic pricing systems. This position is part of the machine learning team within the ...

Machine Learning Engineer I

Seattle, WA ยท On-site

$100K - $150K/yr

About the Role We are looking for a motivated, entry-level Machine Learning Engineer to help build, train, and deploy ML models that power our Marketing AI and AI Sales Agent products. This role is ...

Senior Machine Learning Engineer

Seattle, WA

$118.90K - $163.30K/yr

Access on-demand professional development resources that allow you to hone existing skills and learn new ones "I can succeed as a Machine Learning Engineer at Capital Group" We are seeking a strong ...

Senior Machine Learning Engineer

Seattle, WA ยท On-site

$118.90K - $163.30K/yr

Access on-demand professional development resources that allow you to hone existing skills and learn new ones "I can succeed as a Machine Learning Engineer at Capital Group" We are seeking a strong ...

Sr. Machine Learning Engineer

Seattle, WA

$118.90K - $163.30K/yr

As a Senior Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role in delivering AI-powered features that extract meaningful insights from PitchBook's wealth of ...

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Showing results 1-20

Embedded Machine Learning Engineer information

See Seattle, WA salary details

$79.7K

$174.6K

$198K

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

As of May 30, 2026, the average yearly pay for embedded machine learning engineer 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 are the key skills and qualifications needed to thrive as an Embedded Machine Learning Engineer, and why are they important?

To thrive as an Embedded Machine Learning Engineer, you need expertise in machine learning algorithms, embedded systems programming (C/C++ or Python), and a solid understanding of hardware constraints, usually supported by a degree in computer science, electrical engineering, or related fields. Familiarity with tools like TensorFlow Lite, ONNX, microcontroller SDKs, and experience with real-time operating systems (RTOS) are typically required. Strong problem-solving, communication skills, and the ability to collaborate across multidisciplinary teams help you stand out in this role. These skills are crucial for efficiently deploying intelligent models on resource-constrained devices, ensuring optimal performance and seamless integration in real-world applications.

What are some common challenges faced by Embedded Machine Learning Engineers when deploying models to hardware devices?

One of the main challenges for Embedded Machine Learning Engineers is optimizing machine learning models to run efficiently on devices with limited memory, processing power, and energy capacity. Ensuring real-time performance while maintaining accuracy often requires model quantization, pruning, or using lightweight architectures. Additionally, engineers must carefully manage hardware-software integration and address issues like compatibility with various microcontrollers and ensuring secure, reliable updates for deployed models. Close collaboration with hardware engineers and software developers is essential to overcome these challenges and deliver robust embedded AI solutions.

What does an Embedded Machine Learning Engineer do?

An Embedded Machine Learning Engineer designs and implements machine learning models that can run efficiently on embedded systems, such as microcontrollers and edge devices. Their work involves optimizing algorithms to fit within the resource constraints of these devices, integrating ML models into hardware, and ensuring real-time performance. They collaborate closely with hardware engineers and software developers to deploy intelligent features in products like smart sensors, IoT devices, and autonomous systems.

What is the difference between Embedded Machine Learning Engineer vs Firmware Engineer?

AspectEmbedded Machine Learning EngineerFirmware Engineer
Required CredentialsBachelor's/Master's in Computer Science, Electrical Engineering, or related; knowledge of ML frameworksBachelor's in Electrical Engineering, Computer Engineering, or related; embedded systems experience
Work EnvironmentDevelops ML models for embedded devices, often in IoT or smart devicesDesigns and implements low-level firmware for hardware devices
Industry UsageTech companies, IoT, consumer electronics, automotiveConsumer electronics, automotive, industrial equipment

The Embedded Machine Learning Engineer focuses on integrating machine learning models into embedded systems, while the Firmware Engineer specializes in developing low-level software for hardware devices. Both roles require embedded systems knowledge but differ in their core focus and skill sets.

What are popular job titles related to Embedded Machine Learning Engineer jobs in Seattle, WA? For Embedded Machine Learning Engineer jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Embedded Machine Learning Engineer jobs in Seattle, WA look for? The top searched job categories for Embedded Machine Learning Engineer jobs in Seattle, WA are:
Infographic showing various Embedded Machine Learning Engineer job openings in Seattle, WA as of May 2026, with employment types broken down into 96% Full Time, 2% Part Time, and 2% Contract. Highlights an 92% Physical, and 8% Remote job distribution, with an average salary of $174,554 per year, or $83.9 per hour.
Machine Learning Engineer, Level 4

Machine Learning Engineer, Level 4

Snap Inc.

Bellevue, WA โ€ข On-site

Full-time

Posted 2 days ago


Job description

Job Summary:
Snap Inc is a technology company that aims to enhance communication through its innovative products like Snapchat and augmented reality solutions. They are seeking a Machine Learning Engineer to build and deploy machine learning models for core products, applying modern techniques to solve real-world problems and collaborating with cross-functional teams.
Responsibilities:
โ€ข Build and deploy machine learning models that power core products, serving millions of Snapchatters
โ€ข Apply modern ML techniques to solve large-scale, real-world problems
โ€ข Own the full ML lifecycle from data analysis to production deployment
โ€ข Partner with cross-functional teams to prototype and launch ML-driven features
โ€ข Utilize AI tools to design and ship scalable services while upholding rigorous standards for code correctness, security, and production
Qualifications:
Required:
โ€ข Strong understanding of machine learning approaches and algorithms
โ€ข Able to prioritize duties and work well on your own
โ€ข Ability to work with both internal and external partners
โ€ข Skilled at solving open ambiguous problems
โ€ข Strong collaboration and mentorship skills
โ€ข Proficiency in, or a strong aptitude for, leveraging AI tools to streamline development, paired with the critical judgment to audit generated output for architectural integrity, performance bottlenecks, and security risks
โ€ข Adaptability in learning and applying evolving AI systems and tools to remain at the forefront of engineering trends and modern development practices
โ€ข Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience
โ€ข 3+ years of post-Bachelorโ€™s machine learning experience; or Masterโ€™s degree in a technical field + 2+ year of post-grad machine learning experience; or PhD in a relevant technical field
โ€ข Experience developing machine learning models for ranking, recommendations, search, content understanding, image generation, or other relevant applications of machine learning
Preferred:
โ€ข Advanced degree in computer science or related field
โ€ข Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks
โ€ข Experience working with machine learning, ranking infrastructures, and system design
Company:
Snap is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Founded in 2011, the company is headquartered in Venice, USA, with a team of 5001-10000 employees. The company is currently Late Stage.