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Hourly Embedded Machine Learning Jobs in Seattle, WA

Axon

Sr Machine Learning Engineer I

Seattle, WA · Hybrid

$118K - $163K/yr

Deploy and operate machine learning systems across cloud, edge, and embedded environments. * Monitor production model performance, investigate failures and degradation, and improve models based on ...

Axon

Sr Machine Learning Engineer I

Seattle, WA · Hybrid

$118K - $163K/yr

Your Impact As an Applied Machine Learning Engineer focused on Sensor Fusion & Tracking, you will ... Experience deploying ML systems in production environments (cloud, edge, or embedded systems)

Axon

Sr Machine Learning Engineer I

Seattle, WA · Hybrid

$118K - $163K/yr

Your Impact As an Applied Machine Learning Scientist/Engineer focused on Sensor Fusion & Tracking ... Experience deploying ML systems in production environments (cloud, edge, or embedded systems)

Axon

Senior Machine Learning Scientist

Seattle, WA

$104K - $142K/yr

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI ... IoT devices, or embedded systems is highly desirable. * Excellent problem-solving skills ...

Orchard

Machine Learning Engineer

Seattle, WA · On-site

$120 - $190/hr

We are looking for a Machine Learning Engineer to build creative, practical, and robust solutions ... Experience deploying & optimizing ML models to run fast on embedded compute like NVIDIA Jetson

Orchard Robotics

Machine Learning Engineer

Seattle, WA · On-site

$135K - $210K/yr

We are looking for a Machine Learning Engineer to build creative, practical, and robust solutions ... Experience deploying & optimizing ML models to run fast on embedded compute like NVIDIA Jetson

Orchard Robotics

Machine Learning Engineer

Seattle, WA · On-site

$135K - $210K/yr

We are looking for a Machine Learning Engineer to build creative, practical, and robust solutions ... Experience deploying & optimizing ML models to run fast on embedded compute like NVIDIA Jetson

Axon

Senior Machine Learning Scientist

Seattle, WA · On-site

$104K - $142K/yr

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI ... IoT devices, or embedded systems is highly desirable. * Excellent problem-solving skills ...

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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 11, 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 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.

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 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.

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 Machine Learning Engineer, Wireless Technologies & Ecosystems

Apple Inc.

Seattle, WA • On-site

$140 - $190/hr

Other

Medical, Dental, Retirement

Re-posted 12 days ago

Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

Job description

Embedded Machine Learning Engineer, Wireless Technologies & Ecosystems

Seattle, Washington, United States Software and Services

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.
Minimum Qualifications
  • Bachelor’s degree (3+ years experience) or Master’s degree (2+ years 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.
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.

Benefits include competitive base pay, Apple stock planning options, comprehensive medical and dental coverage, retirement benefits, and educational expense reimbursement.

Apple is an equal‑opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.

We believe accessibility is a fundamental human right. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

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What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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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