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Hourly Embedded Machine Learning Jobs in Washington

The Machine Learning / Data Scientist is a hands-on practitioner with strong capabilities in model ... Familiarity with integrating model outputs into BI tools or applications (e.g., via APIs, embedded ...

... Xometry's embedded DFM AI + IQE integration with Teamcenter and Designcenter. You will be ... machine learning engineering, with a track record of owning and delivering complex ML systems in ...

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Hourly Embedded Machine Learning information

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 the most commonly searched types of Embedded Machine Learning jobs in Washington? The most popular types of Embedded Machine Learning jobs in Washington are:
What job categories do people searching Hourly Embedded Machine Learning jobs in Washington look for? The top searched job categories for Hourly Embedded Machine Learning jobs in Washington are:
What cities in Washington are hiring for Hourly Embedded Machine Learning jobs? Cities in Washington with the most Hourly Embedded Machine Learning job openings:
Infographic showing various Hourly Embedded Machine Learning job openings in Washington as of July 2026, with employment types broken down into 1% Internship, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 83% Physical, 6% Hybrid, and 11% Remote job distribution.

Sr. Staff Embedded AI Engineer

Renesas Electronics

Columbia, MD

$130K - $171K/yr

Full-time

Posted 12 days ago


Job description

Company Description

Renesas is seeking a Sr. Staff Embedded AI Engineer to develop advanced TinyML and embedded AI solutions targeting Renesas microcontroller and MPU platforms (RA, RL78, RX, RZ). This is a highly technical, hands-on role focused on building cloud-based model translation infrastructure and optimizing network inference for resource-constrained embedded systems. You will contribute to a small team developing a service that converts trained machine learning models into efficient C/C++ implementations for deployment on microcontrollers. The ideal candidate combines strong embedded software expertise with solid machine learning fundamentals and is comfortable working across the stack — from neural network internals to low-level performance optimization. You should be someone who contributes new ideas, challenges assumptions, and helps improve both tooling and embedded implementation quality

Job Description
  • BS/MS/PhD in Electrical Engineering, Computer Engineering, Computer Science, or related field. 
  • 6+ years of experience in embedded systems software development.
  • Strong proficiency in C/C++ for embedded platforms. 
  • Strong proficiency in Python for tooling, automation, or ML workflows. 
  • Experience deploying machine learning models to resource-constrained systems. 
  • Solid understanding of neural network fundamentals and internals
  • Experience with machine learning frameworks such as TensorFlow or PyTorch.
  • Experience optimizing performance, memory footprint, and power consumption on embedded targets.
Qualifications

• Experience developing inference runtimes, model translation tools, or code generation systems.
• Experience with CMSIS-NN or other embedded ML acceleration libraries.
• Experience optimizing quantized neural networks for embedded systems using SIMD/DSP acceleration.
• Familiarity with Renesas MCU/MPU platforms (RA, RL78, RX, RZ).
• Experience with real-time systems (RTOS or bare-metal).
• Hardware debugging experience.


Additional Information

Renesas is an embedded semiconductor solution provider driven by its Purpose ‘To Make Our Lives Easier.’ As the industry’s leading expert in embedded processing with unmatched quality and system-level know-how, we have evolved to provide scalable and comprehensive semiconductor solutions for automotive, industrial, infrastructure, and IoT industries based on the broadest product portfolio, including High Performance Computing, Embedded Processing, Analog & Connectivity, and Power.
With a diverse team of over 22,000 professionals in more than 30 countries, we continue to expand our boundaries to offer enhanced user experiences through digitalization and usher into a new era of innovation. We design and develop sustainable, power-efficient solutions today that help people and communities thrive tomorrow, ‘To Make Our Lives Easier.’     
At Renesas, you can: 

  • Launch and advance your career in technical and business roles across four Product Groups and various corporate functions. You will have the opportunities to explore our hardware and software capabilities and try new things.  
  • Make a real impact by developing innovative products and solutions to meet our global customers' evolving needs and help make people’s lives easier, safe and secure. 
  • Maximize your performance and wellbeing in our flexible and inclusive work environment. Our people-first culture and global support system, including the remote work option and Employee Resource Groups, will help you excel from the first day.    

Are you ready to own your success and make your mark?  

Join Renesas. Shape Your Future with Us.  

Renesas Electronics is an equal opportunity and affirmative action employer, committed to celebrating diversity and fostering a work environment free of discrimination on the basis of sex, race, religion, national origin, gender, gender identity, gender expression, age, sexual orientation, military status, veteran status, or any other basis protected by federal, state or local law. For more information, please read our Diversity & Inclusion Statement.

Renesas Electronics deals with dual-use technology that is subject to U.S. export controls regulations. Under these regulations it may be necessary for Renesas to obtain U.S. government export license prior to release of technology to certain persons. The decision whether or not to file or pursue an export license application is at the sole discretion of Renesas.

We have adopted a hybrid model that gives employees the ability to work remotely two days a week while ensuring that we come together as a team in the office the rest of the time. The designated in-office days are Tuesday through Thursday for innovation, collaboration and continuous learning.