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Remote Embedded Machine Learning Jobs in Chicago, IL

D.W. Simpson

Consulting Actuary - Remote

Chicago, IL · On-site +1

$185K/yr

... machine learning. The ideal candidate would have at least 5 years of actuarial experience ... Remote Meet Your Recruiter Arturo Aguilera Director, Social Media & Marketing Arturo joined DW ...

Equity Residential

Product Manager, Data Analytics

Chicago, IL · On-site +1

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... remote work permitted on Fridays. WHAT YOU'LL DO: * Collaborates with business, analytics, and engineering teams to define the vision, strategy, and long-term roadmap for data and machine learning ...

TSMG

AI/ML Data Contributor

Chicago, IL · Remote

... machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format, offering both remote and in-person opportunities (such as device ...

TSMG

AI/ML Data Contributor

Chicago, IL · Remote

... machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format, offering both remote and in-person opportunities (such as device ...

Tempus

Bioinformatics Scientist

Chicago, IL · On-site +1

Develop and refine machine learning models for cell-free circulating tumor DNA fraction estimation ... Additionally, for remote roles open to individuals in unincorporated Los Angeles - including remote ...

Strike Social

Senior Data Scientist

Chicago, IL · Remote

Machine Learning, Real-time Analytics, and Experimental Modeling on the Strike Marketing Cloud/Data ... Working hours are flexible and remote work is encouraged. We are an equal opportunity employer and ...

Performacentric

Full Stack Developer

Chicago, IL · On-site +1

Remote (Preferred: Philippines, Latin America, or North America) Employment Type: Full-Time / ... Candidates with experience in machine learning, large language models (LLMs), AI agents, and ...

Adidev Technologies

AI/ML

Des Plaines, IL · Remote

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... Support, even from afar, with our remote assistance. * Regular salary reviews? You betcha! Ready to ...

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Showing results 21-40

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

Remote Embedded Machine Learning information

See Chicago, IL salary details

$72.1K

$158K

$179.2K

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

As of Aug 19, 2026, the average yearly pay for remote 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 a remote embedded machine learning engineer?

A Remote Embedded Machine Learning Engineer is a professional who develops and deploys machine learning models on embedded systems like microcontrollers, IoT devices, and edge hardware, all while working remotely. Their work involves optimizing algorithms to run efficiently on devices with limited computing power, memory, and battery life. These engineers typically use frameworks such as TensorFlow Lite or TinyML to design intelligent features that operate directly on hardware, enabling real-time decision-making without relying heavily on cloud connectivity. They collaborate with cross-functional teams and often troubleshoot both software and hardware issues from a remote location.

What are the key skills and qualifications needed to thrive as a remote embedded machine learning engineer?

To thrive as a Remote 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 science, electrical engineering, or related fields. Familiarity with microcontrollers, edge AI frameworks (such as TensorFlow Lite or Edge Impulse), and version control systems is typically required. Strong problem-solving skills, effective communication, and self-motivation are essential soft skills for collaborating remotely and troubleshooting complex issues. These skills ensure successful deployment of intelligent solutions on resource-constrained devices and effective teamwork in distributed environments.

What are some common challenges faced by remote embedded machine learning engineers, and how can they be addressed?

Remote Embedded Machine Learning Engineers often encounter challenges related to hardware access, debugging embedded devices remotely, and collaborating with cross-functional teams across time zones. To address these, it's important to set up robust remote development environments, use simulation tools when physical hardware isn't available, and establish clear communication channels for effective teamwork. Regular virtual meetings and detailed documentation also help ensure alignment and smooth progress, despite the remote nature of the work.

What is the difference between Remote Embedded Machine Learning vs Remote Data Scientist?

AspectRemote Embedded Machine LearningRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; experience with embedded systems and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and ML algorithms
Work EnvironmentEmbedded hardware devices, IoT systems, real-time processing environmentsCloud platforms, data analysis labs, remote offices
Employer & Industry UsageTech companies, IoT device manufacturers, automotive, roboticsFinance, healthcare, marketing, tech firms

Remote Embedded Machine Learning specialists focus on integrating ML models into embedded hardware for real-time applications, often working with IoT and robotics. In contrast, Remote Data Scientists analyze large datasets to extract insights, primarily working in cloud or office environments. Both roles require strong analytical skills but differ in technical focus and work settings.

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 Remote Embedded Machine Learning jobs in Chicago, IL?

For Remote Embedded Machine Learning jobs in Chicago, IL, the most frequently searched job titles are:

What job categories do people searching Remote Embedded Machine Learning jobs in Chicago, IL look for?

The top searched job categories for Remote Embedded Machine Learning jobs in Chicago, IL are:

What cities near Chicago, IL are hiring for Remote Embedded Machine Learning jobs?

Cities near Chicago, IL with the most Remote Embedded Machine Learning job openings:

Remote Embedded Machine Learning jobs near you

Digital Signal Processing (DSP) Engineer - AI/ML Ops / Remote

Apetan Consulting llc

Chicago, IL • Remote

$80 - $150/hr

Contractor

Re-posted 7 days ago

Job description

Digital Signal Processing (DSP) Engineer – AI/ML Ops
Location: Chicago, IL (Hybrid/Onsite Preferred)
 
Responsibilities
• Design and implement advanced DSP algorithms for real-time and offline signal processing.
• Develop AI/ML models for signal classification, anomaly detection, feature extraction, and predictive analytics.
• Build scalable data pipelines for signal acquisition, preprocessing, and model training.
• Deploy ML models into production using MLOps best practices.
• Optimize DSP and AI algorithms for latency, throughput, and computational efficiency.
• Collaborate with data scientists, embedded engineers, and software development teams.
• Implement CI/CD pipelines for machine learning workflows.
• Monitor production models for drift, performance, and reliability.
• Work with cloud-native AI services and containerized deployments.
• Document architecture, algorithms, and deployment processes.
 
Required Qualifications
• Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• 5+ years of experience in Digital Signal Processing.
• Strong knowledge of: o Digital Filters o FFT o Wavelets o Spectral Analysis o Adaptive Filtering o Time-Series Signal Processing
• Proficiency in Python and C/C++.
• Experience with TensorFlow or PyTorch.
• Hands-on experience building ML pipelines.
• Experience with Docker and Kubernetes.
• Experience with Git and CI/CD. Preferred Qualifications
• Experience with MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML.
• Experience deploying AI models at the edge.
• Familiarity with NVIDIA CUDA or GPU optimization.
• Experience with audio, radar, RF, image, LiDAR, or sensor signal processing.
• Knowledge of LLMs and Agentic AI is a plus.
• Experience working in regulated industries (Healthcare, Automotive, Aerospace, Telecom, Industrial).