1

Embedded Machine Learning Engineer Jobs in Seattle, WA

Principal Machine Learning Engineer

Redmond, WA ยท On-site

$188K - $304.20K/yr

We are seeking a Principal Machine Learning Engineer to accelerate our training of generative models in close collaboration with Maching Learning (ML) researchers, software engineers, and domain ...

Senior Machine Learning Engineer

Bellevue, WA ยท On-site

$149K - $245K/yr

At Chewy, our Sponsored Ads Technology team based out of Bellevue, WA is looking for a Senior Machine Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite ...

Senior Machine Learning Engineer

Bellevue, WA ยท On-site +1

$149K - $245K/yr

At Chewy, our Sponsored Ads Technology team based out of Bellevue, WA is looking for a Senior Machine Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite ...

At Chewy, our Sponsored Ads Technology team based out of Bellevue, WA is looking for a Staff Machine Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite ...

As a Machine Learning Engineer in the Machine Intelligence Neural Design (MIND) team, you will have an opportunity to be part of an ML innovation organization within Apple that has its roots in the ...

Staff Machine Learning Engineer

Bellevue, WA ยท On-site

$186.50K - $297.50K/yr

At Chewy, our Sponsored Ads Technology team based out of Bellevue, WA is looking for a Staff Machine Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite ...

Senior Machine Learning Engineer

Seattle, WA ยท On-site

$172.50K - $306.63K/yr

What You'll Do As a Senior Machine Learning Engineer on the Content Intelligence team, you will lead the development of ML models and systems, to assist with Content Understanding. You will work ...

Senior Machine Learning Engineer

Seattle, WA ยท Hybrid

$139.40K - $183.80K/yr

Manager, Machine Learning Engineering * Collaborate with scientists and product managers to build proof-of-concepts (POCs) contributing to shaping the Axon of tomorrow. * Architect and develop secure ...

Staff Machine Learning Engineer

Bellevue, WA ยท On-site

$186.50K - $265K/yr

At Chewy, Sponsored Ads team is looking for a Senior Machine Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite sponsored ads. As a member to the Sponsored ...

Staff Machine Learning Engineer

Bellevue, WA ยท On-site

$186.50K - $265K/yr

At Chewy, Sponsored Ads team is looking for a Senior Machine Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite sponsored ads. As a member to the Sponsored ...

next page

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 29, 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, Core Engineering

Machine Learning Engineer, Core Engineering

Pinterest

Seattle, WA โ€ข Remote

$285.98K/yr

Other

Posted 20 days ago


Job description

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace theflexibility to do your best work. Creating a career you love? It's Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 3,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you'll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won't find anywhere else.

What you'll do:

  • Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
  • Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
  • Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
  • Work in a high-impact environment with quick experimentation and product launches
  • Keeping up with industry trends in recommendation systems

What we're looking for:

  • 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
  • End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
  • Degree in computer science, machine learning, statistics, or related field
  • Nice to have:
    • M.S. or PhD in Machine Learning or related areas
    • Publications at top ML conferences
    • Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
    • Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
    • Expertise in scalable realtime systems that process stream data
    • Passion for applied ML and the Pinterest product

Relocation Statement:

  • This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

#LI-SA1

#LI-REMOTE

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

US based applicants only
$138,905โ€”$285,982 USD

Our Commitment to Inclusion:

Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please completethis formfor support.