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Intern Computer Vision Deep Learning Engineer Jobs in North Carolina

... closely with engineers and subjectmatter experts to turn emerging research into practical ... Apply and extend modern deep learning techniques (e.g., convolutional models, 3D vision, attention ...

... closely with engineers and subject-matter experts to turn emerging research into practical ... Apply and extend modern deep learning techniques (e.g., convolutional models, 3D vision, attention ...

New

Machine Learning Engineer About CoVar CoVar is a small AI/ML R&D software company in Durham, NC ... Deep knowledge of state-of-the-art in any of the following: computer vision (preferred), natural ...

Lead AI/ML Engineer - Remote

Raleigh, NC · On-site +1

$99K - $131K/yr

... computer vision, deep learning, and automatic speech recognition (ASR). The engineer applies deep ... learning technologies to enable computers to visualize, learn, and respond to complex situations ...

Lead AI/ML Engineer - Remote

Raleigh, NC · On-site +1

$99K - $131K/yr

... computer vision, deep learning, and automatic speech recognition (ASR). The engineer applies deep ... learning technologies to enable computers to visualize, learn, and respond to complex situations ...

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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 North Carolina? The most popular types of Computer Vision Deep Learning Engineer jobs in North Carolina are:
What job categories do people searching Intern Computer Vision Deep Learning Engineer jobs in North Carolina look for? The top searched job categories for Intern Computer Vision Deep Learning Engineer jobs in North Carolina are:
What cities in North Carolina are hiring for Intern Computer Vision Deep Learning Engineer jobs? Cities in North Carolina with the most Intern Computer Vision Deep Learning Engineer job openings:
Data Scientist (Computer Vision)

Data Scientist (Computer Vision)

SAS

Cary, NC • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

Data Scientist- Hybrid, Cary, North Carolina

We’re a leader in data and AI. Through our software and services, we inspire customers around the world to transform data into intelligence - and questions into answers.

If you're looking for a dynamic, fulfilling career with flexibility and a world-class employee experience, you'll find it here. We're recognized around the world for our inclusive, meaningful culture and innovative technologies by organizations like Fast Company, Forbes, Newsweek and more.

 

About the job

The Applied AI & Modeling (AAIM) team is looking for a Data Scientist to help advance a multiphase applied research and development effort focused on computer vision and machine learning for highimpact realworld data. Our team works at the intersection of advanced modeling, scalable AI systems, and domaindriven problem solving, partnering closely with engineers and subjectmatter experts to turn emerging research into practical, measurable outcomes.

This is an exciting opportunity to build and evaluate stateoftheart vision models while working on problems that demand both technical depth and rigor. You will contribute to the evolution of existing prototypes into more robust, scalable solutions, gaining handson experience with 3D vision, attention mechanisms, and modern deep learning architectures in a collaborative environment. This role is wellsuited for someone who wants to grow as an applied data scientist, learn how advanced AI systems are developed responsibly, and see their work directly influence the next stage of realworld AI innovation.

As a Data Scientist, you will:   

  • Design, develop, and evaluate machine learning and computer vision models to solve complex, realworld problems using large and diverse datasets.
  • Apply and extend modern deep learning techniques (e.g., convolutional models, 3D vision, attention mechanisms, transformerbased approaches) to improve model accuracy, robustness, and scalability.
  • Analyze model performance using appropriate quantitative metrics, identify failure modes, and iterate on solutions based on experimental findings.
  • Collaborate with fellow data scientists, software engineers, and crossfunctional partners to integrate models into endtoend analytical workflows.
  • Contribute to welldocumented, reproducible modeling pipelines and clearly communicate insights, tradeoffs, and results to technical and nontechnical audiences.
  • Ensure all applicable security policies and development processes are followed to support the organization’s secure and responsible software development goals.
  • Embrace curiosity, passion, authenticity, and accountability - our values that guide how we work, learn, and innovate together.

Required qualifications 

  • Master’s degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, or a related quantitative field with a minimum of 3 years of relevant professional experience; or PhD degree in a related quantitative field, with no prior professional work experience required.
  • Demonstrated experience applying computer vision and machine learning techniques to realworld problems, including tasks such as image analysis, feature extraction, model training, and performance evaluation.
  • Handson experience with at least one modern deep learning or computer vision framework (e.g., Pythonbased frameworks commonly used for CNN or visionbased modeling).
  • Experience working with realworld datasets, including data preparation, model evaluation using quantitative metrics, and result interpretation.
  • Ability to analyze results, troubleshoot models, and clearly communicate technical findings to both technical and nontechnical audiences.
  • An equivalent combination of related education, training, and experience may be considered in place of the above qualifications.

Additional competencies, knowledge and skills

 

Key competencies

  • Analytical Thinking – Ability to break down complex, ambiguous problems into structured analytical tasks, evaluate alternative approaches, and use data to support sound technical decisions.
  • Collaboration – Ability to work effectively with crossfunctional partners, including data scientists, engineers, and domain experts, contributing constructively in a teambased environment.
  • Learning Agility – Willingness and ability to quickly learn new methods, tools, and domains, and apply new knowledge to evolving technical challenges.

Additional skills and experience (nice to have)

  • Experience with computer vision techniques for image segmentation, detection, or classification.
  • Exposure to 3D modeling, such as 3D convolutional networks or multidimensional image analysis.
  • Familiarity with attention mechanisms or transformerbased vision models.
  • Experience working in collaborative research and innovative environments.

World-class benefits  

Highlights include...

  • Comprehensive medical, prescription, dental and vision plans.
  • Medical plan options include:
    • PPO with low annual deductible and copays.
    • HDHP combined with a health savings account with a contribution from SAS (no access to on-site health care center).
  • Onsite Health Care Center (HQ) that’s free to employees and family members enrolled in the PPO plan. There's a pharmacy too! Not local to HQ? The pharmacy will ship prescriptions for no additional charge!
  • An industry-leading 401k plan.
  • Tuition Assistance Program and programs and resources to support your development
  • Generous time away including vacation time, a variety of paid holidays, and our much-loved U.S. Winter Wellness Break between December 25 and January 1.
  • Volunteer Time Off, parental leave and unlimited paid sick days.
  • Generous childcare benefits for all full-time employees.

You are welcome here.

At SAS, it’s not about fitting into our culture – it’s about adding to it. We believe our people make the difference. Our inclusive workforce brings together unique talents and inspires teams to create amazing software that reflects the diversity of our users and customers.

Additional Information:

To qualify, applicants must be legally authorized to work in the United States, and should not require, now or in the future, sponsorship for employment visa status. SAS is an equal opportunity employer. All qualified applicants are considered for employment without regard to any characteristic protected by law. Read more: Know Your Rights. 

Resumes may be considered in the order they are received. SAS employees performing certain job functions may require access to technology or software subject to export or import regulations. To comply with these regulations, SAS may obtain nationality or citizenship information from applicants for employment. SAS collects this information solely for trade law compliance purposes and does not use it to discriminate unfairly in the hiring process.

SAS only sends emails from verified “sas.com” email addresses and never asks for sensitive, personal information or money. If you have any doubts about the authenticity of any type of communication from, or on behalf of SAS, please contact Recruitingsupport@sas.com.

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