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Embedded Machine Learning Engineer Jobs in Seattle, WA

Alignerr

Machine Learning Engineer

Seattle, WA · Remote

Machine Learning Engineer (AI Data Trainer) About the Role What if your expertise in machine learning could directly influence how the next generation of AI models reason, plan, and solve complex ...

IUNU

Applied Machine Learning Engineer

Seattle, WA · On-site

Applied Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. To do this job successfully, you need exceptional skills in statistics and ...

IUNU

Applied Machine Learning Engineer

Seattle, WA · On-site

Applied Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. To do this job successfully, you need exceptional skills in statistics and ...

DocuSign

Machine Learning Engineer

Seattle, WA · On-site +1

$164K - $266K/yr

Machine Learning Engineer As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent ...

Robinhood

Machine Learning Engineer

Bellevue, WA

We're looking for an exceptional Machine Learning Engineer to help shape the future of our core platforms, products, and customer experiences. FinTech is one of the most complex and rapidly evolving ...

Robinhood

Machine Learning Engineer

Bellevue, WA

We're looking for an exceptional Machine Learning Engineer to help shape the future of our core platforms, products, and customer experiences. FinTech is one of the most complex and rapidly evolving ...

Robinhood

Machine Learning Engineer

Bellevue, WA · On-site

We're looking for an exceptional Machine Learning Engineer to help shape the future of our core platforms, products, and customer experiences. FinTech is one of the most complex and rapidly evolving ...

DocuSign

Machine Learning Engineer

Seattle, WA · On-site +1

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You ...

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All JobsEmbedded Machine Learning Engineer JobsEmbedded Machine Learning Engineer Jobs in Seattle, WA

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 Jun 19, 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 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 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 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:
Embedded Machine Learning Engineer jobs near you
Infographic showing various Embedded Machine Learning Engineer job openings in Seattle, WA as of June 2026, with employment types broken down into 43% Internship, and 57% Full Time. Highlights an 100% In-person job distribution, with an average salary of $174,554 per year, or $83.9 per hour.
Embedded Machine Learning Engineer, Wireless Technologies & Ecosystems

Embedded Machine Learning Engineer, Wireless Technologies & Ecosystems

Apple

Seattle, WA

$139K - $258K/yr

Full-time

Medical, Dental, Retirement

Posted 24 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers

Job description

Join Apple's innovative iOS Robotics team within Wireless Technologies and Ecosystems (WTE). We're expanding the DockKit Framework's focus on accessories, algorithms, and user experiences to make iOS a leading platform for Perception Algorithm development. As an Embedded Machine Learning Engineer, you'll deploy efficient, low-power ML models directly onto embedded hardware, driving advanced, on-device intelligent experiences for millions of users in robotics and intelligent systems.
Description
This role offers a unique opportunity to innovate at the intersection of AI and embedded hardware. You will transform advanced ML algorithms into highly optimized, power-efficient code for custom silicon and microcontrollers in Apple products, specifically for robotics. You'll tackle complex challenges like memory constraints, computational budgets, and real-time performance, ensuring ML models deliver exceptional user experiences while adhering to Apple’s privacy and power efficiency standards.
","responsibilities":"Design and implement efficient ML inference pipelines on resource-constrained embedded hardware.
Optimize neural network models (e.g., quantization, pruning) for performance, memory, and power on edge devices.
Develop and integrate robust C/C++ low-level software for deploying ML models on microcontrollers, DSPs, and ML accelerators.
Analyze and debug performance bottlenecks and power consumption across the hardware/software stack for ML workloads.
Collaborate with ML researchers, hardware engineers, and platform teams to deliver high-quality, power-efficient edge AI solutions.
Evaluate and recommend embedded platforms, toolchains, and ML frameworks for on-device intelligence applications.
Preferred Qualifications
Experience with ML inference hardware acceleration (DSPs, NPUs, ASICs).Familiarity with diverse neural network architectures and training methodologies for efficient edge deployment.
Knowledge of computer vision, NLP, or audio processing in an embedded/robotics context.
Experience with embedded Linux or other RTOS in a production environment.
Contributions to open-source embedded ML projects or relevant publications.
Proficiency with Python for automation and data analysis.
Minimum Qualifications
Bachelor’s degree (3+ years experience) or Master’s degree (2+ year experience) in CS, EE, or a related technical field.
Proficiency in C/C++ for embedded systems development, including RTOS, microcontrollers, and low-level hardware interactions.
Proven ability to optimize and deploy ML models for resource-constrained edge devices using techniques like - quantization/pruning and frameworks (e.g., TensorFlow Lite, ONNX Runtime, Core ML).
Strong analytical and debugging skills to resolve performance bottlenecks across hardware, firmware, and ML inference.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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