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Intern Computer Vision Deep Learning Engineer Jobs in New Hudson, MI

Wayve

Machine Learning Engineer, App SW

Detroit, MI · Hybrid

$283K - $381K/yr

The Role As an ML Engineer within the Application Engineering team, you'll lead critical ... Expert in deep learning (esp. sequential models, control, planning, or perception). * Proficient in ...

Mariana Minerals

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $180K/yr

We're reimagining the minerals supply chain by combining deep industry expertise with advanced ... As a Machine Learning Engineer at Mariana, you'll help build and improve the machine learning ...

Torc Robotics

Senior, ML Engineer - VLM

Ann Arbor, MI · On-site +1

$102K - $140K/yr

Mentors and guides engineers within the group. * Bachelor's Degree in Computer Science, Robotics ... Computer Vision & Deep Learning - model training and at least two of: 2D/3D Object Detection ...

Torc Robotics

Senior, ML Engineer - VLM

Ann Arbor, MI · On-site +1

$102K - $140K/yr

Mentors and guides engineers within the group. * Bachelor's Degree in Computer Science, Robotics ... Computer Vision & Deep Learning - model training and at least two of: 2D/3D Object Detection ...

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All JobsIntern Computer Vision Deep Learning Engineer JobsIntern Computer Vision Deep Learning Engineer Jobs in New Hudson, MI

Intern Computer Vision Deep Learning Engineer information

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How much do intern computer vision deep learning engineer jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for intern computer vision deep learning engineer in New Hudson, MI is $17.28, according to ZipRecruiter salary data. Most workers in this role earn between $14.62 and $19.52 per hour, depending on experience, location, and employer.

What does an intern computer vision deep learning engineer do?

An Intern Computer Vision Deep Learning Engineer assists in developing and improving algorithms that enable computers to interpret and understand visual information from the world, such as images and videos. They often work on tasks like image classification, object detection, and facial recognition using deep learning frameworks like TensorFlow or PyTorch. Interns typically help with data collection, model training, evaluation, and sometimes deployment, all under the guidance of experienced team members. This role is a great opportunity to gain hands-on experience in machine learning and computer vision while contributing to real-world projects.

What are the key skills and qualifications needed to thrive as an intern computer vision deep learning engineer?

To thrive as an Intern Computer Vision Deep Learning Engineer, you need a solid understanding of machine learning fundamentals, computer vision concepts, and proficiency in programming languages like Python, often supported by coursework or personal projects. Familiarity with deep learning frameworks such as TensorFlow or PyTorch and experience with image processing libraries like OpenCV are typically expected. Strong problem-solving abilities, curiosity, and effective teamwork skills help interns excel in fast-paced research and development environments. These skills are essential for contributing to innovative projects and adapting to the rapidly evolving field of computer vision.

What types of projects or tasks can I expect to work on as an intern computer vision deep learning engineer?

As an Intern Computer Vision Deep Learning Engineer, you can expect to contribute to projects involving image or video analysis, such as object detection, image classification, or facial recognition. Your daily tasks might include data preprocessing, annotating datasets, training and evaluating deep learning models, and assisting with model optimization for deployment. You’ll often work closely with senior engineers and researchers, gaining hands-on experience with real-world datasets and cutting-edge frameworks. Collaboration with cross-functional teams, such as software developers and product managers, is common to ensure your models address practical business needs.

What is the difference between Intern Computer Vision Deep Learning Engineer vs Intern Machine Learning Engineer?

AspectIntern Computer Vision Deep Learning EngineerIntern Machine Learning Engineer
Required SkillsComputer vision, deep learning, CNNs, Python, TensorFlow/PyTorchMachine learning, algorithms, Python, scikit-learn, TensorFlow/PyTorch
Work EnvironmentResearch labs, tech companies, startups focusing on image/video analysisTech companies, research labs, startups working on diverse ML applications
Industry UsagePrimarily in computer vision projects like object detection, image segmentationBroader ML projects including predictive modeling, NLP, recommendation systems

Intern Computer Vision Deep Learning Engineers focus on image and video analysis using deep learning techniques, while Intern Machine Learning Engineers work on a wider range of ML applications. Both roles require strong Python skills and familiarity with deep learning frameworks, but their project focus and industry applications differ.

What cities near New Hudson, MI are hiring for Intern Computer Vision Deep Learning Engineer jobs?

Cities near New Hudson, MI with the most Intern Computer Vision Deep Learning Engineer job openings:

Intern Computer Vision Deep Learning Engineer jobs near you
Infographic showing various Intern Computer Vision Deep Learning Engineer job openings in New Hudson, MI as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 16% Part Time, and 6% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $35,950 per year, or $17.3 per hour.

Senior Robotic AI-Perception Engineer - Only W2

Saransh Inc

Warren, MI • On-site

$98K - $134K/yr

Contractor

Re-posted 15 days ago

Job description

Role: Senior Robotic AI-Perception Engineer
Location: Warren, MI (Onsite from Day 1)
Job Type: W2 Contract
 
Main Skills: Senior Robotic AI-Perception Engineer (AI/ML, perception, computer vision, Python, TensorFlow and/or PyTorch)
 
Key Responsibilities:
· Design, develop, and implement perception algorithms for segmentation, scene understanding, object detection and localization, classification, and dynamic tracking.
· Integrate AI and computer vision algorithms with ROS (Robot Operating System) for real-time deployment on autonomous robots (e.g., mobile manipulators).
· Design and maintain cloud-based pipelines for data collection, annotation, preprocessing, model training, and evaluation.
· Collaborate with hardware engineers, software engineers, and domain experts to integrate with mapping, motion planning, and controls.
· Develop offline tools to test and validate perception models in both simulation and real-world environments.
· Stay updated with emerging technologies and best practices in robotic perception; lead and participate in academic and industrial collaborations.
· Generate intellectual property, document results, and publish papers.
 
Required Qualifications:
· Passion for robotics and a strong desire to accelerate the application of robotics with AI.
· Master’s or Ph.D. in Computer Science, Electrical Engineering, Robotics, or a related field (or Bachelor’s degree with exceptional track record).
· 3+ years of experience developing and deploying AI/ML, perception, and computer vision (e.g., mono and stereo cameras, RGB-D, event camera, LiDAR) on robotic systems.
· Proficiency in Python or C++ with hands-on experience in deep learning frameworks such as TensorFlow and PyTorch.
· Solid understanding of robotics fundamentals, perception and navigation methods (e.g., SLAM, planning), and their typical strengths and shortcomings.
· Consistently seeks opportunities and embraces challenges to drive self-growth and improvement.
 
Preferred Qualifications:
· Ph.D. in Computer Science, Machine Learning, Robotics, Computer Vision, or a related research field.
· Hands-on robotics experience, such as autonomous vehicles (AV), ADAS, or industrial automation systems in manufacturing environments.
· Experience with robotics frameworks such as ROS/ROS2 (e.g., Nav2, MoveIt).
· Understanding of CI/CD pipelines and modern software development practices.