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Machine Learning Infrastructure Engineer Jobs in Illinois

This role will be highly hands-on and infrastructure-first, focused on designing, building, and ... a Machine Learning Engineer, ML Platform Engineer, MLOps Engineer, Applied Scientist or similar ...

Troubleshoot and resolve issues related to ML model performance, data quality, and infrastructure ... machine learning concepts, algorithms, and frameworks. * Knowledge of software engineering ...

New

Senior Machine Learning Engineer

Chicago, IL ยท On-site

$107K - $147K/yr

... infrastructure-as-code pattern. โ€ข Implement data processing workflows to enhance our Feature ... Machine Learning Engineering. โ€ข Partner with data architecture, data governance, and security ...

Hardware Machine Learning Engineer

Chicago, IL ยท On-site

$200K - $225K/yr

We build the hardware, the software, and the infrastructure, so when you hit a bottleneck, you can ... machine learning, and engineering shape how modern markets are traded. A stabilizing force in ...

Hardware Machine Learning Engineer

Chicago, IL ยท On-site

$200K - $225K/yr

We build the hardware, the software, and the infrastructure, so when you hit a bottleneck, you can ... machine learning, and engineering shape how modern markets are traded. A stabilizing force in ...

As an AI & Machine Learning Engineer, you will design, build, and deploy intelligent systems for ... infrastructure (MLflow, Weights & Biases) โ€ข Integrate ML models with ROS2-based robot control for ...

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 ...

Lead Machine Learning Engineer

Chicago, IL ยท On-site

$105K - $139K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Inform your ML infrastructure decisions using your understanding of ML modeling techniques and ...

Hardware Machine Learning Engineer

Chicago, IL ยท On-site

$127K - $167K/yr

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... We build the hardware, the software, and the infrastructure, so when you hit a bottleneck, you can ...

Lead Machine Learning Engineer

Chicago, IL ยท On-site +1

$105K - $139K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Inform your ML infrastructure decisions using your understanding of ML modeling techniques and ...

Lead Machine Learning Engineer

Chicago, IL ยท On-site

$105K - $139K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Inform your ML infrastructure decisions using your understanding of ML modeling techniques and ...

Lead Machine Learning Engineer

Chicago, IL ยท On-site +1

$105K - $139K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Inform your ML infrastructure decisions using your understanding of ML modeling techniques and ...

Senior Machine Learning Engineer

Chicago, IL ยท On-site

$107K - $147K/yr

Implement and productionize final solutions via infrastructure-as-code pattern. Implement data ... respect to Machine Learning Engineering. Partner with data architecture, data governance, and ...

Senior Machine Learning Engineer

Chicago, IL ยท On-site

$107K - $147K/yr

This role will be highly hands-on and infrastructure-first, focused on designing, building, and ... a Machine Learning Engineer, ML Platform Engineer, MLOps Engineer, Applied Scientist or similar ...

Showing results 21-40

Machine Learning Infrastructure Engineer information

See Illinois salary details

$45.1K

$123.1K

$176.4K

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

As of Sep 14, 2026, the average yearly pay for machine learning infrastructure engineer in Illinois is $123,130.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,200.00 and $136,600.00 per year, depending on experience, location, and employer.

What is a machine learning infrastructure engineer?

A Machine Learning Infrastructure Engineer designs, builds, and maintains the systems that support the development and deployment of machine learning models. This includes managing data pipelines, optimizing model training and inference, and ensuring scalability and reliability in production environments. They work closely with data scientists, ML engineers, and DevOps teams to create efficient workflows and infrastructure. Key technologies often include cloud platforms, containerization, orchestration tools, and distributed computing frameworks.

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

To thrive as a Machine Learning Infrastructure Engineer, you need a strong background in computer science, cloud computing, distributed systems, and experience with machine learning frameworks, often supported by a degree in a related field. Familiarity with tools such as Docker, Kubernetes, Terraform, as well as cloud platforms like AWS, GCP, or Azure, and certifications in cloud or DevOps technologies are highly valued. Strong problem-solving abilities, effective communication, and collaboration skills help engineers work seamlessly with data scientists and cross-functional teams. These skills are essential to design, implement, and maintain robust, scalable infrastructure that enables efficient machine learning development and deployment.

What are some common challenges faced by machine learning infrastructure engineers, and how can these be addressed on the job?

Machine Learning Infrastructure Engineers often face challenges such as ensuring infrastructure scalability, managing resource allocation, and maintaining system reliability while supporting rapid experimentation by data science teams. Balancing the needs for flexibility in research environments with production-grade stability requires a deep understanding of both engineering best practices and the unique requirements of machine learning workflows. Collaboration with data scientists, clear communication about infrastructure capabilities, and staying current with fast-evolving technologies are key strategies for success. Most companies encourage ongoing learning and provide opportunities to contribute to architecture decisions, which makes this a rewarding environment for problem-solvers and innovators.

What cities in Illinois are hiring for Machine Learning Infrastructure Engineer jobs?

Cities in Illinois with the most Machine Learning Infrastructure Engineer job openings:

Infographic showing various Machine Learning Infrastructure Engineer job openings in Illinois as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $123,130 per year, or $59.2 per hour.

AI & Machine Learning Engineer

Northbrook, IL โ€ข On-site

Other

Re-posted 25 days ago


Job description

About LightSpeed

LightSpeed Build Technologies is revolutionizing the construction industry through AI-powered robotics. Our flagship systemsโ€”BRUTE for automated wall panel manufacturing and DEX for on-site collaborative constructionโ€”are addressing the global housing crisis by delivering unprecedented speed, precision, and affordability in homebuilding.

Position Overview:

As an AI & Machine Learning Engineer, you will design, build, and deploy the intelligent systems that make LightSpeedโ€™s construction robots smarter, faster, and more autonomous. You will develop machine learning models for computer vision, predictive analytics, autonomous decisionโ€‘making, and process optimizationโ€”all deployed in realโ€‘time production environments where precision and reliability are critical. This role sits at the intersection of cuttingโ€‘edge AI research and practical industrial application.

What you'll work on:

Machine Learning Development

  • 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 realโ€‘time quality monitoring during automated assembly

  • Optimize model inference for edge deployment on GPUโ€‘accelerated hardware in production

Computer Vision & Perception

  • Develop deep learning pipelines for object detection, segmentation, and pose estimation

  • Build realโ€‘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

Data Infrastructure & MLOps

  • 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)

Integration & Deployment

  • Integrate ML models with ROS2-based robot control for realโ€‘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

Required Qualifications:

AI/ML Expertise

  • 4+ years handsโ€‘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)

Software Engineering

  • Strong Python with experience in C++ for performanceโ€‘critical components

  • Experience with ML infrastructure: data pipelines, experiment tracking, model serving

  • Proficiency with Linux, Docker, Git, and CI/CD workflows

  • Understanding of realโ€‘time system constraints for ML inference in production

Preferred Qualifications:
  • 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 MLโ€‘powered robotics

  • Published research or patents in computer vision, robot learning, or related ML

  • Experience with NVIDIA ecosystem: CUDA, cuDNN, TensorRT, Jetson platforms

Why Join LightSpeed:
  • Build AI systems that directly control physical robots addressing the housing crisis

  • Work on rare realโ€‘world ML challenges: realโ€‘time inference, embodied AI, industrial perception

  • Access to rich proprietary datasets from production robot cells

  • Handsโ€‘on culture with direct access to robots, sensors, and manufacturing environments

  • Competitive compensation including salary, equity, and comprehensive benefits

Employment Relationship

This position is atโ€‘will, meaning either you or the Company may terminate employment at any time, with or without cause or notice.

Equal Opportunity

LightSpeed Build Technologies is an equal opportunity employer committed to building a diverse and inclusive workplace. We welcome candidates from all backgrounds and experiences.

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