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Entry Level Machine Learning Engineer Jobs in Waukegan, IL

Aquabyte

Embedded Software Engineer

Mundelein, IL

$130K - $190K/yr

Through custom underwater cameras, computer vision, and machine learning we are able to quantify ... Edge engineering is responsible for the hardware and software orchestrating the hardware installed ...

Just In Time Staffing LLC

Be Seen First

Grinding Machine Operator

Arlington Heights, IL · On-site

$18 - $26/hr

CNC / Honing / Grinding Machine Operator Pay: $18 - $26/hr (Entry level to 2 years experience; negotiable for setup/programming) Shift: 1st Shift (6:00 AM-2:30 PM preferred) or 2nd Shift (8:00 AM-4 ...

KenkoTech Futures

AI Scientist

Mundelein, IL · On-site

PhD in Machine Learning, Computer Science, Computational Biology, Bioinformatics, Statistics ... Strong programming skills using modern ML frameworks (PyTorch, JAX, etc.) * Experience with ...

TekCommands Inc

GCP Site Reliability Engineer

Buffalo Grove, IL · Remote

$58.25 - $77.50/hr

Python, PySpark, or Machine Learning experience. * Experience with Tidal, ServiceNow, xMatters, Ab ... Site Reliability Engineering (SRE) & Incident Management * Prometheus, Grafana & Splunk Monitoring ...

RACINE RAILROAD PRODUCTS INC

CONTROLS ENGINEER

Racine, WI · On-site

$78K - $101K/yr

Experience with machine learning technologies, Neural Networks, or other AI related software. * Experience with both Linux and Windows operating systems. * Familiar with Programming language MATLAB ...

New

RACINE RAILROAD PRODUCTS INC

CONTROLS ENGINEER

Racine, WI · On-site

$78K - $101K/yr

Experience with machine learning technologies, Neural Networks, or other AI related software. * Experience with both Linux and Windows operating systems. * Familiar with Programming language MATLAB ...

New

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All JobsMachine Learning Engineer JobsEntry Level Machine Learning Engineer JobsEntry Level Machine Learning Engineer Jobs in Waukegan, IL

Entry Level Machine Learning Engineer information

See Waukegan, IL salary details

$28.5K

$65.9K

$112.1K

How much do entry level machine learning engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for entry level machine learning engineer in Waukegan, IL is $65,912.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,900.00 and $74,600.00 per year, depending on experience, location, and employer.

What is an entry level machine learning engineer?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are some typical projects or tasks an entry level machine learning engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What are the key skills and qualifications needed to thrive as an entry level machine learning engineer?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are popular job titles related to Entry Level Machine Learning Engineer jobs in Waukegan, IL?

For Entry Level Machine Learning Engineer jobs in Waukegan, IL, the most frequently searched job titles are:

What cities near Waukegan, IL are hiring for Entry Level Machine Learning Engineer jobs?

Cities near Waukegan, IL with the most Entry Level Machine Learning Engineer job openings:

Entry Level Machine Learning Engineer jobs near you
Infographic showing various Entry Level Machine Learning Engineer job openings in Waukegan, IL as of August 2026, with employment types broken down into 15% Internship, and 85% Full Time. Highlights an 72% In-person, 14% Hybrid, and 14% Remote job distribution, with an average salary of $65,912 per year, or $31.7 per hour.

Embedded Software Engineer

Aquabyte

Mundelein, IL

$130K - $190K/yr

Full-time

Re-posted 9 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.