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Intern Computer Vision Deep Learning Engineer Jobs in Kentucky

Augusta Hitech

$125 - $150/hr

United States Role Summary We are seeking a highly skilled Computer Vision Engineer to design ... Optimize deep learning models for edge deployment using hardware acceleration to meet strict cycle ...

Qualcomm

$150 - $200/hr

Job Area Engineering Group, Engineering Group > Video Systems, HW Architecture General Summary ... The team develops next-generation mobile computer vision and deep learning solutions for imaging ...

KLA-Belgium

$150 - $200/hr

... Deep Learning Algorithm Engineer who is passionate about pioneering Deep Learning (DL), foundation ... and computer vision applications in the semiconductor process control business. Qualified ...

Woven

$150 - $200/hr

MINIMUM QUALIFICATIONS MS or PhD in Machine Learning, Computer Vision, Robotics or related ... Deep understanding of runtime complexity, distributed/cloud ML infrastructure, data pipeline ...

Blue River Technology

$200 - $250/hr

Implement deep-learning models and frameworks for scene segmentation, depth estimation, active ... Train and optimize computer vision models for object detection, semantic segmentation, and ...

Xident B.V.

$150 - $200/hr

... with focus on computer vision * Deep expertise in face recognition architectures (ArcFace, CosFace, or similar) * Strong PyTorch skills with experience exporting to ONNX for edge deployment

Society of Defense Financial Management

$125 - $150/hr

We design and implement algorithms to perform pattern recognition, such as statistical and deep ... Previous signal processing, computer vision, or machine learning experience. * Experience ...

New

Bobyard, Inc.

$150 - $200/hr

Join the team building computer vision applications for the construction trades. Contractors spend ... Strong CV + deep learning background -- you've trained and shipped models (segmentation, detection ...

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... applications of computer vision Must Have Experience * Experience with deep learning and ...

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... applications of computer vision Must Have Experience * Experience with deep learning and ...

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... applications of computer vision Must Have Experience * Experience with deep learning and ...

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... applications of computer vision Must Have Experience * Experience with deep learning and ...

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

Intern Computer Vision Deep Learning Engineer information

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 are popular job titles related to Intern Computer Vision Deep Learning Engineer jobs in Kentucky?

For Intern Computer Vision Deep Learning Engineer jobs in Kentucky, the most frequently searched job titles are:

What job categories do people searching Intern Computer Vision Deep Learning Engineer jobs in Kentucky look for?

The top searched job categories for Intern Computer Vision Deep Learning Engineer jobs in Kentucky are:

Intern Computer Vision Deep Learning Engineer jobs near you

Computer Vision Engineer

On-site

Augusta Hitech
IT Services • 51 - 200 employees
Learn more about Augusta Hitechexternal

$125 - $150/hr

Other

Posted 7 days ago

Key responsibilities

  • Design, develop, and deploy real-time defect detection systems for industrial automation pipelines.

  • Integrate high-speed cameras, industrial PCs, and PLCs to capture, process, and label data at high throughput.

  • Implement object detection and image classification algorithms to identify micro-defects on production lines.

Job description

Required Skills: C++, Computer Vision, PyTorch, Tensor

Country: United States

Role Summary

We are seeking a highly skilled Computer Vision Engineer to design, develop, and deploy real-time defect detection systems for our industrial automation pipelines. In this role, you will bridge the gap between advanced machine learning models and physical manufacturing hardware. You will be responsible for integrating high-speed cameras, Industrial PCs (IPCs), and Programmable Logic Controllers (PLCs) to capture, process, and label data at high throughput, ensuring zero-defect quality control on the production floor.

Key Responsibilities

Design and implement robust object detection and image classification algorithms specifically tuned for identifying micro-defects on fast-moving production lines.

Integrate and calibrate high-speed industrial cameras, specialized lighting, and optical setups to ensure optimal image quality for the vision models.

Establish low-latency communication pipelines between the computer vision systems and PLCs to trigger physical sorting or rejection mechanisms in real-time.

Optimize deep learning models for edge deployment using hardware acceleration to meet strict cycle-time requirements.

Develop and maintain automated data collection and labeling pipelines to continuously feed and improve the accuracy of the defect detection models.

Troubleshoot system performance on the manufacturing floor, addressing issues related to camera triggering, lighting fluctuations, and model drift.

Required Programming Languages

C++: Essential for writing highly optimized, multithreaded applications necessary for real-time, low-latency image processing and inferencing on the edge.

Python: Required for rapidly prototyping, training, testing, and refining deep learning models, as well as managing the data processing and labeling scripts.

Structured Text / Ladder Logic (Familiarity): While not strictly required to be an expert, a working knowledge of IEC 61131-3 PLC programming languages is crucial for effectively communicating and designing handshakes with automation engineers.

Required Experience & Technical Skills

High-Speed Imaging Hardware: Proven hands-on experience with industrial camera interfaces (GigE Vision, CoaXPress, Camera Link), frame grabbers, and industrial optics.

Industrial Communication Protocols: Experience seamlessly passing data between Windows/Linux edge computers and PLCs using protocols like OPC UA, Modbus TCP/IP, Ethernet/IP, or PROFINET.

Computer Vision & Deep Learning Frameworks: Deep practical knowledge of traditional computer vision (OpenCV) alongside modern deep learning frameworks (PyTorch, TensorFlow) and architectures suited for fast inference (e.g., YOLO variants).

Hardware Acceleration & Edge AI: Proven ability to deploy models onto industrial hardware (NVIDIA Jetson, x86 IPCs) using optimization toolkits like TensorRT or OpenVINO to maximize frame rates.

Real-Time System Design: Experience dealing with the complexities of concurrent processing, memory management, and preventing frame drops in continuous, 24/7 manufacturing environments.

Data Pipeline Management: Familiarity with tools and best practices for versioning datasets, managing synthetic data generation, and coordinating efficient image labeling workflows for quality control.

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