ZipRecruiter

Log In

1

Embedded Machine Learning Jobs in Chicago, IL (NOW HIRING)

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

Schaumburg, IL · On-site

$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 ...

OceanComm, Inc.

Engineering Intern / Co-op

Chicago, IL · On-site

$35 - $55/hr

... machine learning, embedded systems, and robotics. You can pick a primary area while still having room to cross over. We'll match projects to your skills and curiosity. You'll work closely with ...

New

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 ...

Marmon

Data Scientist

Carol Stream, IL · Hybrid

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

Encore

Senior Azure AI Platform Engineer

Schiller Park, IL · On-site

$122K - $161K/yr

This role focuses on creating the foundational services, patterns, and infrastructure that enable machine learning and generative AI features to be safely and effectively embedded across Encore ...

next page

Showing results 1-20

All JobsEmbedded Machine Learning JobsEmbedded Machine Learning Jobs in Chicago, IL

Embedded Machine Learning information

See Chicago, IL salary details

$72.1K

$158K

$179.2K

How much do embedded machine learning jobs pay per year?

As of Jun 18, 2026, the average yearly pay for embedded machine learning in Chicago, IL is $158,007.00, according to ZipRecruiter salary data. Most workers in this role earn between $135,500.00 and $178,200.00 per year, depending on experience, location, and employer.

Will AI replace embedded programmers?

Embedded machine learning involves developing algorithms for resource-constrained devices, and while AI tools can assist with coding and optimization, embedded programmers are essential for designing, implementing, and maintaining these systems. AI is more likely to augment their work rather than fully replace them, especially given the need for specialized knowledge of hardware and real-time constraints.

Is embedded AI a good career?

Embedded machine learning involves developing AI models for hardware with limited resources, such as IoT devices and embedded systems. It is a growing field with demand for skills in hardware programming, C/C++, and AI frameworks, offering opportunities in industries like automotive, healthcare, and consumer electronics.

Is embedded systems still a good career in 2026?

Embedded Machine Learning remains a strong career in 2026 as industries increasingly adopt AI-powered devices and IoT solutions. Professionals with skills in hardware programming, real-time systems, and machine learning frameworks like TensorFlow Lite are in demand for developing intelligent embedded applications. Continuous learning and familiarity with microcontrollers, sensors, and embedded software development are essential for long-term growth in this field.

What engineers make $500,000?

Senior engineers in specialized fields such as embedded machine learning, AI, or data science can reach salaries of $500,000 or more, especially with extensive experience, advanced skills in programming and hardware, and leadership roles. High compensation often involves working in high-demand industries, with additional bonuses or stock options contributing to total earnings.

What are some common challenges faced by professionals working in embedded machine learning roles?

Professionals in embedded machine learning roles often face the challenge of optimizing machine learning models to run efficiently on resource-constrained hardware, such as microcontrollers or edge devices with limited memory and processing power. Balancing model accuracy, inference speed, and energy consumption can require creative problem-solving and deep knowledge of both hardware and software. Additionally, collaboration with hardware engineers, data scientists, and software developers is key, as projects typically require cross-functional teamwork to meet performance and deployment goals. Staying current with rapidly evolving tools and best practices is also important in this dynamic field.

What is an Embedded Machine Learning job?

An Embedded Machine Learning job involves developing and optimizing machine learning models to run efficiently on resource-constrained devices like microcontrollers, edge devices, and IoT hardware. Professionals in this role work on model compression, low-power inference, and real-time processing, ensuring AI capabilities can function without relying on cloud computing. Responsibilities often include data preprocessing, feature extraction, model training, and deployment on embedded systems using frameworks like TensorFlow Lite or Edge Impulse.

What are the key skills and qualifications needed to thrive in the Embedded Machine Learning position, and why are they important?

To thrive in Embedded Machine Learning, you should have expertise in machine learning algorithms, embedded systems programming (e.g., C/C++, Python), and a solid understanding of hardware-software integration, typically backed by a degree in computer engineering, electrical engineering, or a related field. Familiarity with edge AI tools (such as TensorFlow Lite, ONNX, or Edge Impulse), microcontrollers, and real-time operating systems is highly valued, alongside relevant certifications such as Embedded Systems or AI certificates. Strong problem-solving skills, effective communication, and the ability to work cross-functionally are crucial soft skills in this field. These qualifications and qualities are vital for creating efficient, reliable AI solutions that operate seamlessly within resource-constrained environments and interdisciplinary project teams.

What are the most commonly searched types of Embedded Machine Learning jobs in Chicago, IL? The most popular types of Embedded Machine Learning jobs in Chicago, IL are:
What are popular job titles related to Embedded Machine Learning jobs in Chicago, IL? For Embedded Machine Learning jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Embedded Machine Learning jobs in Chicago, IL look for? The top searched job categories for Embedded Machine Learning jobs in Chicago, IL are:
Embedded Machine Learning jobs near you
Infographic showing various Embedded Machine Learning job openings in Chicago, IL as of June 2026, with employment types broken down into 76% Full Time, 7% Part Time, 4% Temporary, 4% Contract, and 9% Nights. Highlights an 91% Physical, 4% Hybrid, and 5% Remote job distribution, with an average salary of $158,007 per year, or $76 per hour.

Embedded Software Engineer

Aquabyte

Mundelein, IL

$134K - $176K/yr

Full-time

Posted 4 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 and identifying potential inconsistencies or verification signals in application materials based on available information. 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.