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Intern Computer Vision Deep Learning Engineer Jobs in Michigan

Optimal Inc.

ML Engineer

Warren, MI · On-site

Machine Learning Engineer Job Summary We are seeking a Machine Learning Engineer with strong expertise in machine learning, deep learning, and computer vision. The ideal candidate will have ...

New

Optimal Inc.

ML Engineer

Warren, MI · On-site

Machine Learning Engineer Job Summary We are seeking a Machine Learning Engineer with strong expertise in machine learning, deep learning, and computer vision. The ideal candidate will have ...

Eccalon LLC

AI Expert Robotics - onsite

Detroit, MI

Collaborate with mechanical, electrical, and software engineering teams to ensure end-to-end system ... Experience with computer vision, deep learning, or reinforcement learning * Familiarity with ...

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All JobsIntern Computer Vision Deep Learning Engineer JobsIntern Computer Vision Deep Learning Engineer Jobs in Michigan

Intern Computer Vision Deep Learning Engineer information

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 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 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, and why are they important?

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 are the most commonly searched types of Computer Vision Deep Learning Engineer jobs in Michigan? The most popular types of Computer Vision Deep Learning Engineer jobs in Michigan are:
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Intern Computer Vision Deep Learning Engineer jobs near you
Senior Perception Engineer - Computer Vision & 3D Deep Learning IRC295016

Senior Perception Engineer - Computer Vision & 3D Deep Learning IRC295016

GlobalLogic

Northville, MI • On-site

$99K - $136K/yr

Full-time

Posted 8 days ago

GlobalLogic rating

7.5

Company rating: 7.5 out of 10

Based on 11 frontline employees who took The Breakroom Quiz

123rd of 191 rated software companies

Job description

Job Summary:
GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world’s largest companies. They are seeking a Senior Perception Engineer specializing in computer vision and deep learning, responsible for designing and implementing algorithms for object detection and segmentation using camera and LiDAR data fusion.
Responsibilities:
• Design and implement computer vision algorithms for object detection and segmentation using camera and LiDAR data fusion.
• Develop deep learning models for 2D and 3D object detection, including implementation and optimization of YOLO, Faster R-CNN, SSD, and transformer-based architectures.
• Create and optimize LiDAR point cloud processing pipelines using PCL and Open3D for 3D object detection and segmentation.
• Implement sensor fusion techniques to combine camera and LiDAR data for enhanced object detection accuracy.
• Develop instance and semantic segmentation algorithms using state-of-the-art models like Mask R-CNN, U-Net, and DeepLab.
• Implement and optimize deep learning models specifically designed for LiDAR point clouds, including PointNet, PointNet++, and other 3D neural network architectures.
• Develop robust perception algorithms that maintain performance in adverse weather conditions such as rain, snow, fog, and low-light scenarios.
• Build and maintain computer vision pipelines using OpenCV for image preprocessing, feature extraction, and geometric transformations.
• Design and implement multi-object tracking systems using Kalman filtering, SORT, and DeepSORT algorithms.
• Work with ROS2 for integration and deployment of perception algorithms.
• Optimize deep learning models for edge deployment and real-time inference performance.
• Develop robust evaluation metrics and testing frameworks for object detection systems.
• Collaborate with cross-functional teams to integrate perception algorithms into larger autonomous systems.
• Stay up-to-date with industry trends and emerging technologies to innovate and improve perception systems.
Qualifications:
Required:
• Strong expertise in computer vision and deep learning for object detection and segmentation tasks.
• Proficiency in deep learning frameworks (PyTorch and TensorFlow) with hands-on experience implementing detection models (YOLO, Faster R-CNN, SSD, RetinaNet, Detectron, etc.).
• Extensive experience with OpenCV for image processing and computer vision applications.
• Solid background in 3D perception using LiDAR point clouds; proficiency with PCL and Open3D libraries.
• Familiarity with LiDAR-specific deep learning models such as PointNet, PointNet++, VoxelNet, and other point cloud neural network architectures.
• Experience in developing and improving perception models for adverse weather conditions (rain, snow, fog) including domain adaptation and robust feature extraction techniques.
• Experience with sensor fusion techniques for combining camera and LiDAR data streams.
• Strong programming skills in Python and C++ for algorithm development and optimization.
• Experience with model optimization techniques for real-time inference.
• Familiarity with 3D geometry, coordinate transformations, and spatial data processing.
• Knowledge of evaluation metrics for object detection and tracking systems (mAP, IoU, custom metrics, etc.).
Company:
GlobalLogic is a product development services company that specializes in chip-to-cloud software engineering. It is a sub-organization of Hitachi. Founded in 2000, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.

What GlobalLogic employees say

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Hours and flexibility

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