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Hourly Embedded Machine Learning Jobs in Seattle, WA

Meta

Product Manager, Machine Learning

Seattle, WA

$146K/yr

Product Manager, Machine Learning Responsibilities: * Plan, initiate, and manage information ... Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual ...

MedBridge, Inc.

Head of Data and Machine Learning

WA · On-site

... embedded in workflows rather than bolted on. Communicate complex technical strategy clearly to ... Machine learning and modeling: Advanced Python, classical and deep learning, NLP with transformers ...

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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 Jun 9, 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
Product Manager, Machine Learning

Product Manager, Machine Learning

Meta

Seattle, WA

$146K/yr

Full-time

Posted 7 days ago

Meta rating

7.5

Company rating: 7.5 out of 10

Based on 43 frontline employees who took The Breakroom Quiz

120th of 186 rated software companies

Job description

In this role, you will develop and execute a strategy to enhance Ad supply personalization on FB App. You will spearhead innovative approaches to predict user engagement and optimize ad value, significantly boosting the efficiency and accuracy of our ad supply system.
Product Manager, Machine Learning Responsibilities:
  • Plan, initiate, and manage information technology projects for web-based products and platforms
  • Lead the ideation, technical development, and launch of innovative tools, platforms, and/or products
  • Drive product development with teams of world-class engineers and designers, while maintaining team health
  • Work closely with cross-functional teams to drive product vision, define product requirements, coordinate resources from other groups (design, legal, etc.), and guide the team through key milestones
  • Integrate usability studies, research, and market analysis into product requirements to improve engineer productivity and enhance user satisfaction
  • Define and analyze metrics that inform the success of products. Identify and track key performance metrics
  • Understand Facebook’s strategic and competitive position and deliver products that are aligned with our mission and recognized best in the industry
  • Maximize efficiency in a constantly evolving environment where the process is fluid and creative solutions are the norm

Minimum Qualifications:
  • 5+ years product management or related industry experience
  • Product management or related industry experience in one of the following areas: Machine Learning based personalization, ranking or recommendations services, or ad-tech
  • Requires a Bachelor's degree (or foreign degree equivalent) in Computer Science, Engineering, Information Systems, Analytics, Mathematics, Physics, Applied Sciences, or a related field and 2+ years of experience in the following:
  • Experience product management or product design
  • Experience working in a technical environment with a broad, cross functional team to drive product vision, define product requirements, coordinate resources from other groups (design, legal, etc.), and guide the team through key milestones
  • Experience delivering technical presentations
  • Experience analyzing complex, large-scale data sets and making decisions based on data
  • Experience gathering requirements across diverse areas and users, and converting and developing them into a product solution
  • Technical experience with analytical tools, methodologies, and design
  • Displaying leadership, organizational and execution skills
  • Proven communication skills

Preferred Qualifications:
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$146,000/year to $204,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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