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Machine Learning Biomedical Engineer Jobs in Vernon Hills, IL

Hardware Machine Learning Engineer

Chicago, IL ยท On-site

$127K - $167K/yr

... engineers to implement, verify, and deploy ML inference solutions from proof-of-concept through production * Track and evaluate emerging research in neural architecture search, machine learning ...

Hardware Machine Learning Engineer

Chicago, IL ยท On-site

$200K - $225K/yr

  • PTO

... engineers to implement, verify, and deploy ML inference solutions from proof-of-concept through production * Track and evaluate emerging research in neural architecture search, machine learning ...

Manager Machine Learning Engineering

Schaumburg, IL ยท On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Our machine learning engineering team is responsible for developing infrastructure and tooling to help enable data driven decisions and insights at scale for millions of Paylocity users. Our team is:

Hardware Machine Learning Engineer

Chicago, IL ยท On-site

$200K - $225K/yr

  • PTO

... engineers to implement, verify, and deploy ML inference solutions from proof-of-concept through production * Track and evaluate emerging research in neural architecture search, machine learning ...

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Biomedical Engineering tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have ...

Showing results 21-40

Machine Learning Biomedical Engineer information

See Vernon Hills, IL salary details

$30.7K

$125.4K

$188.5K

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

As of Aug 18, 2026, the average yearly pay for machine learning biomedical engineer in Vernon Hills, IL is $125,443.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,900.00 and $151,000.00 per year, depending on experience, location, and employer.

What does a machine learning biomedical engineer do?

A Machine Learning Biomedical Engineer applies machine learning techniques to solve problems in biology and medicine. They develop algorithms and models to analyze complex biomedical data, such as medical images, genetic information, or sensor readings. Their work supports advancements in diagnostics, treatment planning, and personalized medicine. Typically, they collaborate with clinicians, researchers, and other engineers to design systems that improve healthcare outcomes.

How does a machine learning biomedical engineer typically collaborate with clinicians and researchers in a healthcare setting?

Machine Learning Biomedical Engineers often work closely with clinicians and researchers to develop algorithms that solve real-world medical challenges. Collaboration usually involves understanding clinical needs, translating them into technical requirements, and iteratively refining models based on feedback from medical experts. Regular meetings, interdisciplinary project teams, and direct participation in data collection or validation studies are common. This collaborative environment ensures that technical solutions are both innovative and clinically relevant, making communication and adaptability essential skills.

What are the key skills and qualifications needed to thrive as a machine learning biomedical engineer, and why are they important?

To thrive as a Machine Learning Biomedical Engineer, you need a strong background in biomedical engineering, data analysis, and machine learning, typically supported by a degree in biomedical engineering, computer science, or a related field. Familiarity with programming languages like Python or R, machine learning frameworks (e.g., TensorFlow, PyTorch), and experience with medical imaging or signal processing tools are commonly required. Critical thinking, problem-solving, and the ability to communicate complex technical concepts to interdisciplinary teams are vital soft skills. These abilities are crucial for developing innovative healthcare solutions, ensuring regulatory compliance, and bridging the gap between technology and medicine.

What is the difference between Machine Learning Biomedical Engineer vs Data Scientist in Biomedical Industry?

AspectMachine Learning Biomedical EngineerData Scientist in Biomedical Industry
Required CredentialsDegree in Biomedical Engineering, Computer Science, or related fields; knowledge of machine learning and biomedical dataDegree in Data Science, Statistics, or related fields; proficiency in data analysis and machine learning
Work EnvironmentResearch labs, healthcare institutions, biotech companiesHealthcare analytics firms, research institutions, biotech companies
Employer & Industry UsageDevelops algorithms for medical devices, diagnostics, and treatment planningAnalyzes biomedical data to inform clinical decisions, research, and product development

Both roles require expertise in machine learning and biomedical data, but Machine Learning Biomedical Engineers focus on developing algorithms for medical applications, while Data Scientists analyze biomedical data to support research and clinical decisions.

What are popular job titles related to Machine Learning Biomedical Engineer jobs in Vernon Hills, IL?

For Machine Learning Biomedical Engineer jobs in Vernon Hills, IL, the most frequently searched job titles are:

What cities near Vernon Hills, IL are hiring for Machine Learning Biomedical Engineer jobs?

Cities near Vernon Hills, IL with the most Machine Learning Biomedical Engineer job openings:

Infographic showing various Machine Learning Biomedical Engineer job openings in Vernon Hills, IL as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $125,443 per year, or $60.3 per hour.

AI & Machine Learning Engineer

Lightspeed

Northbrook, IL โ€ข On-site

Full-time

Posted 28 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:
โ€ข Design, train, and deploy ML models for robotic control, quality prediction, and process optimization
โ€ข Develop reinforcement learning and imitation learning systems for robot task planning
โ€ข Build predictive maintenance models using sensor data to anticipate equipment failures
โ€ข Implement anomaly detection for real-time quality monitoring during automated assembly
โ€ข Optimize model inference for edge deployment on GPU-accelerated hardware in production
โ€ข Develop deep learning pipelines for object detection, segmentation, and pose estimation
โ€ข Build real-time vision systems for robotic guidance, workpiece tracking, and dimensional verification
โ€ข Implement 3D point cloud processing for construction material recognition
โ€ข Design and train models for visual quality inspection using depth cameras and industrial imaging
โ€ข Build ML data pipelines from sensor acquisition through model training and deployment
โ€ข Establish data labeling, versioning, and management workflows for training datasets
โ€ข Implement model monitoring, A/B testing, and continuous improvement in production
โ€ข Design experiment tracking and reproducibility infrastructure (MLflow, Weights & Biases)
โ€ข Integrate ML models with ROS2-based robot control for real-time inference
โ€ข Optimize models for NVIDIA Jetson, industrial PCs, and edge computing platforms
โ€ข Collaborate with robotics engineers on sensor selection, placement, and calibration
โ€ข Support scaling ML systems across multiple production cells and sites
Qualifications:
Required:
โ€ข 4+ years hands-on ML engineering building and deploying production models
โ€ข Deep proficiency with PyTorch or TensorFlow for model development and training
โ€ข Strong computer vision experience: object detection, segmentation, depth estimation, or 3D vision
โ€ข Understanding of reinforcement learning, imitation learning, or robot learning approaches
โ€ข Experience optimizing ML models for edge deployment (TensorRT, ONNX, quantization)
โ€ข Strong Python with experience in C++ for performance-critical components
โ€ข Experience with ML infrastructure: data pipelines, experiment tracking, model serving
โ€ข Proficiency with Linux, Docker, Git, and CI/CD workflows
โ€ข Understanding of real-time system constraints for ML inference in production
Preferred:
โ€ข MS or PhD in Machine Learning, Computer Science, Robotics, or related field
โ€ข Experience with robotics simulation: MuJoCo, IsaacSIM, or similar
โ€ข Background in manufacturing, industrial automation, or construction technology
โ€ข Experience with ROS/ROS2 integration for ML-powered robotics
โ€ข Published research or patents in computer vision, robot learning, or related ML
โ€ข 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.