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Embedded Machine Learning Engineer Jobs in Chicago, IL

Gotion, Inc.

Machine Learning Engineer

Manteno, IL · On-site

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

AppFolio

Sr. Machine Learning Engineer

Chicago, IL · Remote

$107.60K - $147.80K/yr

Assistant : a GenAI copilot embedded across the product experience * Flows: an agentic workflow ... Who we are looking for We're seeking a Sr Machine Learning Engineer to play a critical role in ...

Reyes Coca-Cola Bottling

Machine Learning Engineer

Niles, IL · On-site

$53 - $72.75/hr

Hands-on experience with CI/CD pipelines, automation tools, and version control systems like Azure DevOps, Github, or similar and strong understanding of machine learning concepts and the ML ...

Apex Systems

Senior Machine Learning Engineer

Chicago, IL · On-site

$107.70K - $147.90K/yr

The client seeks an extraordinary Machine Learning Engineer to help build the algorithmic assets and features that client guests, members, customers and internal users leverage to transform the guest ...

Allied

Senior Machine Learning Engineer

Chicago, IL · On-site +1

$150K - $185K/yr

POSITION SUMMARY The Senior Machine Learning Engineer is responsible for designing, building, and deploying scalable machine learning systems that drive business impact. This role will partner ...

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Embedded Machine Learning Engineer information

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$72.1K

$158K

$179.2K

How much do embedded machine learning engineer jobs pay per year?

As of May 31, 2026, the average yearly pay for embedded machine learning engineer 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.

What are the key skills and qualifications needed to thrive as an Embedded Machine Learning Engineer, and why are they important?

To thrive as an Embedded Machine Learning Engineer, you need expertise in machine learning algorithms, embedded systems programming (C/C++ or Python), and a solid understanding of hardware constraints, usually supported by a degree in computer science, electrical engineering, or related fields. Familiarity with tools like TensorFlow Lite, ONNX, microcontroller SDKs, and experience with real-time operating systems (RTOS) are typically required. Strong problem-solving, communication skills, and the ability to collaborate across multidisciplinary teams help you stand out in this role. These skills are crucial for efficiently deploying intelligent models on resource-constrained devices, ensuring optimal performance and seamless integration in real-world applications.

What are some common challenges faced by Embedded Machine Learning Engineers when deploying models to hardware devices?

One of the main challenges for Embedded Machine Learning Engineers is optimizing machine learning models to run efficiently on devices with limited memory, processing power, and energy capacity. Ensuring real-time performance while maintaining accuracy often requires model quantization, pruning, or using lightweight architectures. Additionally, engineers must carefully manage hardware-software integration and address issues like compatibility with various microcontrollers and ensuring secure, reliable updates for deployed models. Close collaboration with hardware engineers and software developers is essential to overcome these challenges and deliver robust embedded AI solutions.

What does an Embedded Machine Learning Engineer do?

An Embedded Machine Learning Engineer designs and implements machine learning models that can run efficiently on embedded systems, such as microcontrollers and edge devices. Their work involves optimizing algorithms to fit within the resource constraints of these devices, integrating ML models into hardware, and ensuring real-time performance. They collaborate closely with hardware engineers and software developers to deploy intelligent features in products like smart sensors, IoT devices, and autonomous systems.

What is the difference between Embedded Machine Learning Engineer vs Firmware Engineer?

AspectEmbedded Machine Learning EngineerFirmware Engineer
Required CredentialsBachelor's/Master's in Computer Science, Electrical Engineering, or related; knowledge of ML frameworksBachelor's in Electrical Engineering, Computer Engineering, or related; embedded systems experience
Work EnvironmentDevelops ML models for embedded devices, often in IoT or smart devicesDesigns and implements low-level firmware for hardware devices
Industry UsageTech companies, IoT, consumer electronics, automotiveConsumer electronics, automotive, industrial equipment

The Embedded Machine Learning Engineer focuses on integrating machine learning models into embedded systems, while the Firmware Engineer specializes in developing low-level software for hardware devices. Both roles require embedded systems knowledge but differ in their core focus and skill sets.

What are popular job titles related to Embedded Machine Learning Engineer jobs in Chicago, IL? For Embedded Machine Learning Engineer jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Embedded Machine Learning Engineer jobs in Chicago, IL look for? The top searched job categories for Embedded Machine Learning Engineer jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Embedded Machine Learning Engineer jobs? Cities near Chicago, IL with the most Embedded Machine Learning Engineer job openings:
Embedded Machine Learning Engineer jobs near you
Infographic showing various Embedded Machine Learning Engineer job openings in Chicago, IL as of May 2026, with employment types broken down into 6% Internship, 88% Full Time, and 6% Contract. Highlights an 63% In-person, 6% Hybrid, and 31% Remote job distribution, with an average salary of $158,007 per year, or $76 per hour.
Machine Learning Engineer

Machine Learning Engineer

Gotion, Inc.

Manteno, IL • On-site

Full-time

Posted 22 days ago

Job description

Gotion Inc. is based in Silicon Valley, CA, currently building a Manufacturing facility in Manteno, IL and has R&D centers in Ohio, China, Japan and Europe. We innovate in the next generation electric vehicle and energy storage technologies (lithium batteries and related systems) with the aim to accelerate electrified transportation and achieve sustainable development. Gotion is powered by a leading power battery technology company that provides solutions for vehicles including the world's first mass commercial e-bus route.
Gotion is a career destination - we are not simply attempting to just fill another job, but to pursue a dream of global green energy together! We offer outstanding opportunities to individuals seeking an exciting and challenging working environment. Everyone is highly valued and plays a vital role in the growth of our organization.
About The TeamThe Product Development Team at Gotion Illinois New Energy Inc. focuses on the design and development of advanced battery products for next-generation energy storage system (ESS) and electric vehicle (EV) applications. We lead the full product development cycle, integrating mechanical, electrical, thermal, and control system to create high-performance battery solutions, along with comprehensive system integration, validation, and certification activities.
Role Summary
We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains such as battery technology, energy systems, or related physical sciences. This is a fully on-site role based in Manteno, IL focused on building innovative ML models from the ground up.
You will collaborate closely with cross-disciplinary R&D teams to develop and deploy machine learning solutions that address real-world challenges in advanced materials, electrochemical systems, and high-throughput data environments.
Essential Duties and Responsibilities:
  • Design and implement novel machine learning and deep learning models tailored to internal research needs
  • Prototype and evaluate state-of-the-art algorithms, including Transformers, LLMs, and hybrid model architectures
  • Conduct rigorous experimentation, benchmarking, and ablation studies
  • Collaborate with battery scientists and domain experts to incorporate physical constraints or scientific priors into modeling
  • Contribute to internal documentation and present research outcomes to technical and leadership teams
  • Track and integrate advances from the ML research community to ensure technical excellence

Required Qualifications:
  • Ph.D. (preferred) or M.S. in Machine Learning, Computer Science, Electrical Engineering, Applied Mathematics, or a closely related field
  • Demonstrated expertise in model development, optimization, and algorithmic innovation
  • Proficiency in Python and ML libraries/frameworks such as PyTorch, TensorFlow, etc.
  • Solid understanding of learning theory concepts such as regularization, generalization, loss functions, and evaluation metrics
  • Experience working with scientific or time-series datasets, especially in battery, materials, or energy domains, is highly desirable
  • A publication record in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR, CVPR) is a strong plus
  • Excellent communication, collaboration, and problem-solving skills in interdisciplinary environments

The US base salary range for this full-time position is $80,000.00 - $90,000.00 + 15% bonus + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Gotion Inc. is proud to be an equal opportunity employer. We are dedicated to fostering a diverse workforce that reflects the communities we serve, cultivating a culture of inclusion and belonging, and ensuring equal employment opportunities for all.
We provide equal opportunity to all individuals regardless of race, creed, color, religion, gender, sexual orientation, gender identity or expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related conditions (including breastfeeding), parental status, criminal histories consistent with legal requirements, or any other characteristic protected by law.
At Gotion Inc., we strive to create an environment where everyone feels valued, respected, and empowered to thrive.

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