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

Understanding of multiples OS's, including Windows, Linux, Windows Embedded, or NI-OS ? Familiarity with machine learning algorithms for vision problems ? Strong personal self-discipline as well as ...

Technical Program Manager

Chicago, IL · On-site

$85K - $92K/yr

... embedded systems, AI infrastructure, machine learning, semiconductor, and next-generation edge computing platforms. This role will lead complex hardware and software development programs from concept ...

Technical Program Manager

Chicago, IL · On-site +1

$89K - $110K/hr

... embedded systems, AI infrastructure, machine learning, semiconductor, and next-generation edge computing platforms. This role will lead complex hardware and software development programs from concept ...

... embedded with business experts in Crowe's AI team * Document findings and provide strategic ... Helps senior team members test simple machine learning or AI scripts using existing frameworks or ...

Serve as a senior customer-facing voice for Pacvue on AI, machine learning, Pacvue Agent, agentic ... Ensure AI is embedded into core product workflows rather than treated as a standalone feature or ...

Emerging Tech: Experience with Machine Learning systems, algorithm management, and real-time/embedded programming. Modern Methodology: Familiarity with Agile, version control, and automating ...

Emerging Tech: Experience with Machine Learning systems, algorithm management, and real-time/embedded programming. Modern Methodology: Familiarity with Agile, version control, and automating ...

Emerging Tech: Experience with Machine Learning systems, algorithm management, and real-time/embedded programming. Modern Methodology: Familiarity with Agile, version control, and automating ...

Showing results 41-60

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 Sep 1, 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.

What is an embedded machine learning?

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 embedded machine learning?

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 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 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:

Infographic showing various Embedded Machine Learning job openings in Chicago, IL as of August 2026, with employment types broken down into 9% Internship, 82% Full Time, and 9% Contract. Highlights an 100% In-person job distribution, with an average salary of $158,007 per year, or $76 per hour.

Forward Deployed Engineer AI & Healthcare Technology

Rush University Medical Center

Chicago, IL

$41.88 - $62.40/hr

Full-time

Posted 7 days ago


Rush University Medical Center rating

8.1

Company rating: 8.1 out of 10

Based on 109 frontline employees who took The Breakroom Quiz

117th of 1,064 rated hospitals


Job description

Location: Chicago, Illinois

Business Unit: Rush Medical Center

Hospital: Rush University Medical Center

Department: Enterprise IT Strategy & Plang

Work Type: Full Time (Total FTE between 0. 9 and 1. 0)

Shift: Shift 1

Work Schedule: 8 Hr (8:00:00 AM - 5:00:00 PM)

Rush offers exceptional rewards and benefits learn more at our Rush benefits page (https://www.rush.edu/rush-careers/employee-benefits).

Pay Range: $41.88 - $62.40 per hour
Rush salaries are determined by many factors including, but not limited to, education, job-related experience and skills, as well as internal equity and industry specific market data. The pay range for each role reflects Rush’s anticipated wage or salary reasonably expected to be offered for the position. Offers may vary depending on the circumstances of each case.

Summary:

The Forward Deployed Engineer – AI & Healthcare Technology is a high-impact engineering role at the forefront of Rush’s AI transformation. Embedded within a rapid-response, cross-functional “tiger team,” this position turns emerging AI capabilities into practical, production-ready solutions that improve patient care, enhance operational efficiency, and support better decision-making across the enterprise.

Working at the intersection of software engineering, artificial intelligence, and healthcare, the Forward Deployed Engineer partners directly with clinicians, business leaders, executives, data scientists, and IT teams to understand complex challenges and rapidly design, build, integrate, and deploy solutions. This includes connecting AI models and applications with enterprise platforms such as Epic, Salesforce, Workday, ServiceNow, PACS, and data platforms, as well as developing APIs, data pipelines, and scalable system integrations.

This role is ideal for a hands-on engineer who enjoys solving complex problems and moving quickly from concept to production. The successful candidate will bring strong coding and integration skills, experience with AI/ML and emerging technologies such as generative AI, NLP, and large language models, and the ability to translate technical concepts into solutions that work in real-world healthcare environments. Experience with cloud platforms such as AWS, Azure, or GCP is also important.

Beyond building technology, the Forward Deployed Engineer will help ensure solutions are secure, scalable, reliable, and aligned with healthcare regulations and enterprise architecture. The role will also support user adoption through demonstrations, training, documentation, and collaboration with clinical and operational teams.

If you are energized by emerging technology, enjoy working directly with customers and stakeholders, and want to see your engineering work make a tangible difference in healthcare, this is an opportunity to help shape how AI is developed and deployed across Rush.

Responsibilities:
1. Solution Deployment & Integration

  • Partner with operational and administrative stakeholders
  • Help deploy AI solutions in real-world healthcare environments
  • Connect AI models to existing healthcare systems like Epic, Salesforce, Workday and Service now, PACS, and data platforms
  • Build reliable APIs, data pipelines, and system integrations

2. AI / Machine Learning Support

  • Turn business and clinical problems into AI-based solutions
  • Customize and improve machine learning models for healthcare use cases
  • Partner with data scientists to move models from testing into production

3. Working with Stakeholders

  • Serve as a technical partner to executives, clinicians, and IT leaders
  • Gather requirements and turn them into clear technical designs
  • Lead working sessions, demos, and design discussions with different teams

4. Innovation & Prototyping

  • Quickly build and test new AI ideas, such as clinical decision tools or workflow automation
  • Try new technologies like generative AI, natural language processing, and computer vision
  • Review and test new tools to see if they can be used across the organization

5. System Design & Performance

  • Design solutions that are secure, scalable, and compliant with healthcare regulations
  • Improve performance and reliability of AI systems once they are live
  • Set up monitoring and support continuous improvement

6. Change Management & Adoption

  • Help teams adopt new AI tools and workflows
  • Train users and technical teams on new solutions
  • Create clear documentation, guides, and best practices

Required Job Qualifications

  • Bachelor’s degree in Computer Science, Engineering, or a related field OR 2 or more years of experience in software development, system integration, or AI solutions
  • Experience working with healthcare IT systems (such as Epic, Salesforce, Workday, Service Now, HL7, FHIR, PACS, VNA)
  • Strong coding skills, Natural Language Processing, Gen AI and large language models and understanding of APIs
  • Experience using cloud platforms like AWS, Azure, or GCP
  • Experience deploying AI or machine learning solutions

Competencies:

  • Strong Technical Skills: Able to build real solutions, not just prototypes
  • Customer Focus: Understands the needs of clinicians and healthcare teams
  • Adaptability: Comfortable working in changing and unclear environments
  • Clear Communication: Can explain technical ideas to non-technical audiences
  • Problem Solving: Thinks logically and works through complex challenges

Rush is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics.


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