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Hourly Embedded Machine Learning Jobs in Seattle, WA

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)

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... machine learning to solve real-world challenges in a traditionally underserved industry. Their ... As a Sr. Software Engineer, Embedded Systems, you will work alongside your software, mechanical and ...

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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 Jul 1, 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 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:
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.
Sr Machine Learning Engineer I

Sr Machine Learning Engineer I

Axon

Seattle, WA • On-site

$150K - $241K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted yesterday


Axon rating

8.8

Company rating: 8.8 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

8th of 141 rated electronics manufacturers


Job description

Join Axon and be a Force for Good.
At Axon, we're on a mission to Protect Life. We're explorers, pursuing society's most critical safety and justice issues with our ecosystem of devices and cloud software. Like our products, we work better together. We connect with candor and care, seeking out diverse perspectives from our customers, communities and each other.
Life at Axon is fast-paced, challenging and meaningful. Here, you'll take ownership and drive real change. Constantly grow as you work hard for a mission that matters at a company where you matter.
Your Impact
As an Applied Machine Learning Engineer focused on Sensor Fusion & Tracking, you will research, design, and validate advanced estimation and probabilistic models that power Dedrone's real-time airspace awareness systems. Your work will shape the mathematical foundations behind multi-sensor fusion, multi-target tracking, and uncertainty modeling in complex environments. This role offers the opportunity to translate cutting-edge theory into deployed systems that support critical safety missions worldwide.
What You'll Do
Location: Hybrid from Seattle, WA
  • Research and develop advanced multi-sensor fusion and multi-target tracking methodologies.
  • Design probabilistic models and state estimation frameworks for radar, RF, optical, and other sensing modalities.
  • Develop and evaluate algorithms such as Kalman filters (EKF/UKF), particle filters, Bayesian filters, probabilistic data association, and multi-hypothesis tracking.
  • Conduct simulation studies and performance benchmarking across varying operational conditions and noise environments.
  • Analyze real-world datasets to validate model assumptions, quantify uncertainty, and improve robustness.
  • Partner closely with software engineers to transition validated algorithms into scalable, production-ready systems.
  • Publish internal technical documentation and contribute to intellectual property development where applicable.
  • Stay current with advancements in tracking, estimation theory, probabilistic modeling, and machine learning research.
What You Bring
  • Bachelor's or Master's degree in Computer Science, Electrical Engineering, Applied Mathematics, or related field - or equivalent hands-on experience building ML systems in production.
  • 8+ years of experience developing and deploying machine learning systems in real-world applications.
  • Well-developed proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or similar.
  • Experience deploying ML systems in production environments (cloud, edge, or embedded systems).
  • Solid understanding of statistics, model evaluation, and performance trade-offs.
  • Familiarity with MLOps practices including CI/CD for ML, model versioning, monitoring, and automated retraining workflows.
  • Experience working with large, noisy, or multi-modal datasets.
  • Clear communication skills and a collaborative mindset aligned with Axon's values: Aim Far, Win Right, Own It, Join Forces, and Be Obsessed with the Customer.
Benefits that Benefit You
  • Competitive salary and 401k with employer match
  • Discretionary paid time off
  • Paid parental leave for all
  • Medical, Dental, Vision plans
  • Fitness Programs
  • Emotional & Mental Wellness support
  • Learning & Development programs
  • Employee Resource Groups (ERGs)
  • And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work.
Location: This role is based out of our Seattle, WA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesdays through Fridays, with the flexibility to work remotely on Mondays, unless there is an approved workplace accommodation. We believe that connection fuels innovation, and our in-office culture is designed to foster meaningful teamwork, mentorship, and shared success.
#LI-Hybrid
Axon is a total compensation company, meaning compensation is made up of base pay, bonus, and stock awards. The actual base pay is dependent upon many factors, such as: level, function, training, transferable skills, work experience, business needs, geographic market, and often a combination of all these factors. Our benefits offer an array of options to help support you physically, financially and emotionally through the big milestones and in your everyday life. To see more details on our benefits offerings please visit https://www.axon.com/careers.
Base Pay Range
$150,750-$241,200 USD
Don't meet every single requirement? That's ok. At Axon, we Aim Far. We think big with a long-term view because we want to reinvent the world to be a safer, better place. We are also committed to building diverse teams that reflect the communities we serve.
Studies have shown that women and people of color are less likely to apply to jobs unless they check every box in the job description. If you're excited about this role and our mission to Protect Life but your experience doesn't align perfectly with every qualification listed here, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
Important Notes
The above job description is not intended as, nor should it be construed as, exhaustive of all duties, responsibilities, skills, efforts, or working conditions associated with this job. The job description may change or be supplemented at any time in accordance with business needs and conditions.
Some roles may also require legal eligibility to work in a firearms environment.
We collect personal information from applicants to evaluate candidates for employment. You may request access, deletion, or exercise other CCPA rights at axongreenhousesupport@axon.com or via our Axon Privacy Web Form. For more information, please see the Your California Privacy Rights section of our Applicant and Candidate Privacy Notice.
Axon's mission is to Protect Life and is committed to the well-being and safety of its employees as well as Axon's impact on the environment. All Axon employees must be aware of and committed to the appropriate environmental, health, and safety regulations, policies, and procedures. Axon employees are empowered to report safety concerns as they arise and activities potentially impacting the environment.
We are an equal opportunity employer that promotes justice, advances equity, values diversity and fosters inclusion. We're committed to hiring the best talent - regardless of race, creed, color, ancestry, religion, sex (including pregnancy), national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, genetic information, veteran status, or any other characteristic protected by applicable laws, regulations and ordinances - and empowering all of our employees so they can do their best work. If you have a disability or special need that requires assistance or accommodation during the application or the recruiting process, please email recruitingops@axon.com. Please note that this email address is for accommodation purposes only. Axon will not respond to inquiries for other purposes.
Phishing alert: Axon will never ask you to pay for any part of the hiring process, including training, equipment, or background checks. We do not make job offers via text message, WhatsApp, or instant messaging platforms without a formal interview process. All legitimate job openings are listed on our official careers page at https://www.axon.com/careers. If you receive a suspicious offer or outreach from an email address that is not @axon.com, or if you are asked for sensitive personal information (bank details, Social Security Number) prematurely, please ignore the message and report it to recruitingops@axon.com.

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