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Apprentice Machine Learning Testing Jobs in Chicago, IL

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Proficiency in Python, C++, or similar languages for tooling, testing, and simulation * Strong ...

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Proficiency in Python, C++, or similar languages for tooling, testing, and simulation * Strong ...

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Proficiency in Python, C++, or similar languages for tooling, testing, and simulation * Strong ...

The Hartfordis seeking aSenior AI Machine Learning Engineerwithin Employee Benefits Applied AI and ... Strong hands-on expertise in Python, SQL, SDLC practices, Git-based development, automated testing ...

Manufacturing Apprentice

Elmhurst, IL

$17 - $22/hr

If you're passionate about learning, eager to develop new skills, and excited about working in a ... Support the Team: Assist experienced professionals with machine setup, operation, and maintenance.

Manufacturing Apprentice

Elmhurst, IL

$17 - $22/hr

If you're passionate about learning, eager to develop new skills, and excited about working in a ... Support the Team: Assist experienced professionals with machine setup, operation, and maintenance.

Manufacturing Apprentice

Elmhurst, IL · On-site

$17 - $22/hr

If you're passionate about learning, eager to develop new skills, and excited about working in a ... Support the Team: Assist experienced professionals with machine setup, operation, and maintenance.

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Apprentice Machine Learning Testing information

See Chicago, IL salary details

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How much do apprentice machine learning testing jobs pay per hour?

As of Jul 30, 2026, the average hourly pay for apprentice machine learning testing in Chicago, IL is $19.94, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $21.78 per hour, depending on experience, location, and employer.

What kinds of projects or tasks can I expect to work on as an Apprentice Machine Learning Testing?

As an Apprentice Machine Learning Testing, you’ll typically assist in evaluating machine learning models by designing and running tests, analyzing model outputs, and helping identify issues like bias or overfitting. You may work closely with data scientists and software engineers to validate model performance and ensure results align with project objectives. Your daily tasks might include preparing test datasets, executing automated testing scripts, and documenting findings to help improve model reliability. This role often serves as a valuable introduction to practical machine learning workflows and quality assurance processes in technical teams.

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

To thrive as an Apprentice in Machine Learning Testing, a foundational understanding of statistics, programming (especially Python), and basic machine learning concepts is essential, often supported by a degree or coursework in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, Jupyter Notebooks, and version control systems is typically required. Strong analytical thinking, attention to detail, and effective communication skills help apprentices collaborate and identify testing issues efficiently. These skills ensure accurate model validation, effective troubleshooting, and contribute to the robust deployment of machine learning solutions.

What does an Apprentice Machine Learning Testing do?

An Apprentice Machine Learning Testing professional assists in evaluating and validating machine learning models to ensure they perform as expected. They typically work under the guidance of experienced data scientists or engineers, running tests, analyzing results, and helping to identify issues such as bias or inaccuracies in algorithms. Their responsibilities may also include developing test cases, writing reports, and learning about data preprocessing and evaluation metrics. This role is ideal for those who are new to the field and want to build foundational skills in machine learning quality assurance.

What is the difference between Apprentice Machine Learning Testing vs Machine Learning Engineer?

AspectApprentice Machine Learning TestingMachine Learning Engineer
Required CredentialsBasic understanding of ML concepts, often pursuing relevant certifications or degreesAdvanced degrees (BSc, MSc, PhD) in CS or related fields, with extensive experience
Work EnvironmentEntry-level, supervised testing environments, often in training programsFull-time, independent development and deployment of ML models in production
Employer & Industry UsageInternships, training programs, entry-level roles in tech companiesEstablished tech firms, startups, research institutions

Apprentice Machine Learning Testing roles focus on learning and assisting with testing ML models under supervision, while Machine Learning Engineers design, build, and deploy ML systems independently. The apprentice position is ideal for gaining foundational skills, whereas the engineer role requires advanced expertise and experience.

What are the most commonly searched types of Machine Learning Testing jobs in Chicago, IL? The most popular types of Machine Learning Testing jobs in Chicago, IL are:
What are popular job titles related to Apprentice Machine Learning Testing jobs in Chicago, IL? For Apprentice Machine Learning Testing jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Apprentice Machine Learning Testing jobs in Chicago, IL look for? The top searched job categories for Apprentice Machine Learning Testing jobs in Chicago, IL are:

AI & Machine Learning Engineer

Lightspeed

Northbrook, IL • On-site

Full-time

Posted 8 days ago


Job description

Job Summary:
LightSpeed Build Technologies is revolutionizing the construction industry through AI-powered robotics. As an AI & Machine Learning Engineer, you will design, build, and deploy intelligent systems for construction robots, focusing on machine learning models for computer vision, predictive analytics, and process optimization.
Responsibilities:
• Design, train, and deploy ML models for robotic control, quality prediction, and process optimization
• Develop reinforcement learning and imitation learning systems for robot task planning
• Build predictive maintenance models using sensor data to anticipate equipment failures
• Implement anomaly detection for real-time quality monitoring during automated assembly
• Optimize model inference for edge deployment on GPU-accelerated hardware in production
• Develop deep learning pipelines for object detection, segmentation, and pose estimation
• Build real-time vision systems for robotic guidance, workpiece tracking, and dimensional verification
• Implement 3D point cloud processing for construction material recognition
• Design and train models for visual quality inspection using depth cameras and industrial imaging
• Build ML data pipelines from sensor acquisition through model training and deployment
• Establish data labeling, versioning, and management workflows for training datasets
• Implement model monitoring, A/B testing, and continuous improvement in production
• Design experiment tracking and reproducibility infrastructure (MLflow, Weights & Biases)
• Integrate ML models with ROS2-based robot control for real-time inference
• Optimize models for NVIDIA Jetson, industrial PCs, and edge computing platforms
• Collaborate with robotics engineers on sensor selection, placement, and calibration
• Support scaling ML systems across multiple production cells and sites
Qualifications:
Required:
• 4+ years hands-on ML engineering building and deploying production models
• Deep proficiency with PyTorch or TensorFlow for model development and training
• Strong computer vision experience: object detection, segmentation, depth estimation, or 3D vision
• Understanding of reinforcement learning, imitation learning, or robot learning approaches
• Experience optimizing ML models for edge deployment (TensorRT, ONNX, quantization)
• Strong Python with experience in C++ for performance-critical components
• Experience with ML infrastructure: data pipelines, experiment tracking, model serving
• Proficiency with Linux, Docker, Git, and CI/CD workflows
• Understanding of real-time system constraints for ML inference in production
Preferred:
• MS or PhD in Machine Learning, Computer Science, Robotics, or related field
• Experience with robotics simulation: MuJoCo, IsaacSIM, or similar
• Background in manufacturing, industrial automation, or construction technology
• Experience with ROS/ROS2 integration for ML-powered robotics
• Published research or patents in computer vision, robot learning, or related ML
• Experience with NVIDIA ecosystem: CUDA, cuDNN, TensorRT, Jetson platforms
Company:
BUILDING TOMORROW'S HOMES, FASTER AND SMARTER The Lightspeed Integrated Walls, Floors and Roof Systems are built with advanced software and AI driven industrial robots, allowing us to seamlessly craft the walls, floors and roofs, integrating the framing, MEPs, insulation, and drywall in a single, efficient manufacturing line. Founded in , the company is headquartered in , , with a team of 11-50 employees. The company is currently Early Stage.