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Intern Computer Vision Deep Learning Engineer Jobs in Georgia

Design and implement novel computer vision and deep learning algorithms for virtual staining and ... Knowledge of software engineering best practices including version control (Git) and CI/CD ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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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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 the most commonly searched types of Computer Vision Deep Learning Engineer jobs in Georgia?

The most popular types of Computer Vision Deep Learning Engineer jobs in Georgia are:

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

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

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

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

Computer Vision / Deep Learning Scientist (Atlanta)

Aptonet

Atlanta, GA • On-site

Full-time

Posted yesterday

New


Job description

Computer Vision / Deep Learning Scientist – SeniorPosition Overview

We are seeking a Senior Computer Vision / Deep Learning Scientist to design, develop, and deploy advanced computer vision and deep learning solutions for unique, high-impact applications. The successful candidate will combine strong theoretical knowledge with hands‑on industry experience to develop novel algorithms, custom deep learning architectures, and production‑ready machine learning solutions. This role will be a key contributor to a Digital Train Inspection project, applying computer vision and deep learning techniques to analyze visual data and support automated inspection capabilities.

The Senior Scientist will own the model development lifecycle from requirements gathering and data evaluation through model development, validation, production integration, and post‑production support. The role requires close collaboration with application development teams, business stakeholders, and senior leadership, as well as the ability to provide technical guidance to junior team members and lead targeted research initiatives.

Work Arrangement
  • Hybrid schedule: Two days onsite each week for candidates located in the Atlanta area.
  • Fully remote option available for candidates located outside the Atlanta area.
Key Responsibilities
  • Design, develop, and implement novel computer vision algorithms for specialized and unique use cases.
  • Design and build custom deep learning architectures tailored to specific business and technical requirements.
  • Develop and apply deep learning models for semantic segmentation, object detection, image classification, and related computer vision applications.
  • Evaluate model accuracy, robustness, quality, and performance, as well as the quality and suitability of underlying data sources.
  • Develop clean, scalable, maintainable, and production‑ready Python and machine learning code.
  • Partner with application development teams to integrate computer vision and deep learning models into existing applications and production environments.
  • Own the complete model development lifecycle, including requirements gathering, data assessment, experimentation, model development, validation, deployment, monitoring, and post‑production support.
  • Conduct research and experimentation to identify and implement new computer vision and deep learning techniques.
  • Communicate technical findings, model performance, research results, and recommendations clearly to colleagues, business partners, and senior management.
  • Provide technical guidance and mentorship to junior team members and oversee targeted research and team projects.
  • Contribute to hiring initiatives, including technical candidate evaluation, interviews, and assessment of prospective team members.
  • Collaborate across technical and business functions to translate complex computer vision challenges into practical, scalable solutions.
Required Qualifications
  • Bachelor’s, Master’s, or Ph.D. in Computer Science, Electrical Engineering, Machine Learning, Statistics, or a related technical field.
  • 1–3 years of relevant industry experience in a role such as Computer Vision Scientist, Data Scientist, Research Scientist, Machine Learning Scientist, or similar; 3+ years of experience is preferred. Candidates with equivalent proven qualifications may also be considered.
  • Excellent programming skills in Python, with demonstrated experience developing machine learning or deep learning solutions in an industry environment.
  • Hands‑on industry experience with PyTorch or another major deep learning framework.
  • Strong practical experience applying deep learning techniques to computer vision problems, including semantic segmentation, object detection, and image classification.
  • Ability to evaluate model performance and data quality and translate findings into actionable improvements.
  • Experience developing production‑ready machine learning solutions and collaborating with software/application development teams.
  • Strong analytical, problem‑solving, communication, and research skills.
Preferred Qualifications
  • 3+ years of professional experience in computer vision, machine learning, deep learning, or a closely related discipline.
  • Experience taking machine learning models from research or experimentation into production.
  • Experience working with large‑scale visual datasets and establishing data quality and model evaluation processes.
  • Experience mentoring technical professionals or leading research‑oriented projects.
  • Experience participating in technical recruiting, interviewing, or candidate evaluation.
Project Focus: Digital Train Inspection

The selected candidate will contribute to a Digital Train Inspection initiative, developing computer vision and deep learning capabilities that support automated analysis of train and rail‑related visual inspection data. The work will involve applying advanced image analysis and machine learning techniques to identify, classify, segment, and evaluate visual conditions relevant to inspection and maintenance workflows.

Core Technical Skills
  • Python
  • PyTorch or comparable deep learning frameworks
  • Computer Vision
  • Semantic Segmentation
  • Image Classification
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