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Apprentice Machine Learning Robotics Jobs in Chicago, IL

JLL

Mechatronics and Robotics Apprentice

Monee, IL · On-site

... learning program. Trains in andadheresto all health and safety policies and procedures. Work ... Working in cramped positions under/behind machinery * Working at heights * Pushing/pulling wheeled ...

JLL

Mechatronics & Robotics Apprenticeship

Monee, IL

Mechatronics Junior Technician Apprentice - JLL What this job involves: As a Mechatronics Junior ... Working in cramped positions under/behind machinery * Working at heights * Pushing/pulling wheeled ...

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

As of May 31, 2026, the average hourly pay for apprentice machine learning robotics in Chicago, IL is $22.69, according to ZipRecruiter salary data. Most workers in this role earn between $17.84 and $24.76 per hour, depending on experience, location, and employer.
What are the most commonly searched types of Machine Learning Robotics jobs in Chicago, IL? The most popular types of Machine Learning Robotics jobs in Chicago, IL are:
Apprentice Machine Learning Robotics jobs near you
AI & Machine Learning Engineer

AI & Machine Learning Engineer

Lightspeed

Northbrook, IL • On-site

Full-time

Posted 4 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.

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