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Hourly Embedded Machine Learning Jobs in Illinois

Aquabyte

Embedded Software Engineer

Mundelein, IL

$134K - $176K/yr

Through custom underwater cameras, computer vision, and machine learning we are able to quantify ... Improve our embedded Linux build and deployment process * Develop software to automate hardware ...

Motorola

Embedded Software Engineer (DSP)

Schaumburg, IL · On-site

$63K - $97K/yr

Familiarity with Python is a plus, particularly for automation or in the context of AI/Machine Learning workflows. * Embedded Fundamentals: Experience with ARM-based or DSP microprocessor ...

Motorola

Embedded Software Engineer

Schaumburg, IL

$75K - $150K/yr

... and machine learning, cybersecurity, signals intelligence and more. We can't tell you much more ... Hands-on experience in embedded software development is also beneficial. Our products are developed ...

Uottawa

APTPUO Fall 2026- MIA5100- (ONLINE)

Campus, IL

$239.47/hr

MACHINE LEARNING Course Code: MIA5100 Section: A Course Description: Posting limited to: Professeur ... Hourly Rate: Enseignement / Teaching: $239.47 (2024-2025) The academic year starts on September 1 ...

Uottawa

APTPUO Winter 2027- MIA5100- (ONLINE)

Campus, IL · On-site

$239.47/hr

MACHINE LEARNING Course Code: MIA5100 Section: A Course Description: Posting limited to: Professeur ... Hourly Rate: Enseignement / Teaching: $239.47 (2024-2025) The academic year starts on September 1 ...

Caterpillar

Embedded Software Senior Engineer

Mossville, IL · On-site

$112K - $169K/yr

These applications are deployed on multiple mining machines such as trucks, loaders, dozers, drills ... continuous learning. What You Will Have: • Requirements Analysis: Proficiency in requirements ...

University of Utah

Hourly Research Assistants

Campus, IL

$13.82 - $26.94/hr

Details Open Date 05/07/2026 Requisition Number PRN44959B Job Title Hourly Research Assistants ... Experience applying NLP or machine learning methods to real-world datasets (e.g., clinical text ...

University of Utah

Hourly Research Assistants

Campus, IL

$13.82 - $26.94/hr

Details Open Date 05/07/2026 Requisition Number PRN44959B Job Title Hourly Research Assistants ... Experience applying NLP or machine learning methods to real-world datasets (e.g., clinical text ...

University of Utah

Hourly Research Assistants

Campus, IL · On-site

$13.82 - $26.94/hr

Details Open Date 05/07/2026 Requisition Number PRN44959B Job Title Hourly Research Assistants ... Experience applying NLP or machine learning methods to real-world datasets (e.g., clinical text ...

Marmon Holdings, Inc.

Data Scientist

Carol Stream, IL · On-site

What You'll Do * Translate business requirements into analytical, machine learning, and GenAI ... Hands-on usage of Microsoft Copilot tools (e.g., Copilot for M365, Copilot Studio, or embedded ...

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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 Illinois? The most popular types of Embedded Machine Learning jobs in Illinois are:
What are popular job titles related to Hourly Embedded Machine Learning jobs in Illinois? For Hourly Embedded Machine Learning jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Hourly Embedded Machine Learning jobs in Illinois look for? The top searched job categories for Hourly Embedded Machine Learning jobs in Illinois are:
What cities in Illinois are hiring for Hourly Embedded Machine Learning jobs? Cities in Illinois with the most Hourly Embedded Machine Learning job openings:
Hourly Embedded Machine Learning jobs near you

Embedded Software Engineer

Aquabyte

Mundelein, IL

$134K - $176K/yr

Full-time

Posted 27 days ago

Job description

Our mission 
Aquabyte is on a mission to revolutionize the sustainability and efficiency of aquaculture. By making fish farming cheaper and more viable than livestock production, we aim to mitigate one of the biggest causes of climate change and help prepare our planet for impending population growth. Aquaculture is the single fastest growing food-production sector in the world, and now is the time to define how technology is used to harvest the sea and preserve it for generations to come.
 
We are a diverse, mission-driven team that is eager to work alongside kindred spirits. If this vision makes you smile, gives you goosebumps, or otherwise inspires you please get in touch.
 
Our product
We are currently focused on helping salmon farmers better understand their fish populations and make environmentally-sound decisions. Through custom underwater cameras, computer vision, and machine learning we are able to quantify fish weights, detect the health status, and generate optimal feeding plans in real time. Our product operates at three levels: on-site hardware for image capture, cloud pipelines for data processing, and a user-facing web application. As a result, there are hundreds of moving pieces and no shortage of fascinating challenges across all levels of the stack.
 
About The Edge Systems Team:
Edge engineering is responsible for the hardware and software orchestrating the hardware installed at fish farms around the world. Our goals are to create autonomous, reliable, bandwidth-light, long-lasting, robust, remote-debuggable, fail-safe, and easily deployable underwater cameras and sensors.
 
We work with world-class mechanical engineering firms and optical consultants to spec the underwater equipment we deploy. The edge engineering team writes software and procedures to make quality testing of these cameras as easy as possible for the field team in Norway. The types of tests we orchestrate are hardware burn-in, optical quality testing in-air and in-water, sensor calibration and verification, and stereo camera calibration.
 
The edge team also writes software to make it easy for the field team to successfully deploy and configure our hardware at the farm. As it’s often rainy in Norway and the Internet may not yet be set up, our debugging tools need to operate wirelessly and allow a field technician to interface with the hardware from their phones.
 
The edge team is responsible for designing the network, cellular backup system, and mesh network of devices at a farm. We plan for failure, and build in redundancies where possible. Internet can go out for hours and there’s only so much data we can uplink. Boats may park between our antennas.
 
As Aquabyte evolves, more products will be built on-top of the pixel and sensor data we collect. In order to scale, these algorithms need to live on the edge. We work closely with the machine learning team to help move their algorithms safely from the cloud to the edge.
We are responsible for our own Linux build process and the process of safely deploying software to the devices in the field.
 
This role is flexible and is based out of our Bay Area office and involves occasional travel to Norway and Chile.
Job Responsibilities
  • Interface with sensors; cameras; mesh, wireless, and cellular networks to create robust, reliable, and remote data collection and processing systems
  • Develop on ARM-based embedded platforms using C, C++, python, golang or rust
  • Improve our embedded Linux build and deployment process
  • Develop software to automate hardware testing procedures
  • Build diagnostic and configuration tooling to enable our field team to interface with our hardware wirelessly from their phones.
  • Enable our research team to try new machine learning models on real hardware
  • Participate in hardware specifications for our next generation equipment
  • Participate in on-call for diagnosing and fixing device issues remotely and implementing procedures and tooling to help enable the field team to self-diagnose and fix issues themselves
Qualifications
  • Engineering or CS degree.
  • Software development on an embedded device
  • Experience writing and building software.
  • Professional experience with C, C++, Golang, Python or Rust.
Desired but Not Required
  • Solid understanding of TCP/IP
  • Real-Time Operating Systems (RTOS)
  • Buildroot, Yocto Project, toolchains, uBoot, UART, SPI, I2C interfaces
  • Experience with WiFi, BLE, LoRaWAN, Mesh Networking, Cellular Networks
  • Selecting hardware targeted for harsh environmental conditions
  • Ability to read a schematic
  • Experience with cloud environments such as AWS.
  • Experience deploying to off-site hardware.
  • Professional experience working with cameras.
  • Build and maintain fleet operations tools for monitoring, notifications, trending, and analysis.
  • Experience at a small & quickly growing startup
Benefits
  • Competitive salary and equity
  • Unlimited vacation policy
  • Flexible working hours + hybrid work policy
  • Medical, vision, & dental insurance
  • Retirement matching plan
  • Potential travel to Norway
  • Evolve in a fast-paced environment
  • Be able to shape a business in its early days
  • Get ideas, feedback, and suggestions from other best-in-their-field colleagues
  • Mentorship opportunities, we'll be dedicated to investing in you and supporting you as you grow
Aquabyte takes a market-based approach to compensation. The pay varies on a variety of factors including: job-related qualification, years of experience and competence level, interview performance, and work location.
At Aquabyte, we admire interesting people with a unique background. We strongly encourage you to apply even if you don’t satisfy all the requirements, and we will get back to you as soon as possible! 

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.