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Intern Computer Vision Deep Learning Engineer Jobs in Baltimore, MD

Razor Talent

Machine Learning Engineer

Columbia, MD

$2.0K/mo

Machine Learning Engineer Our clients, a rapidly growing AI-focused software development company ... S. citizenship Preferred Qualifications • Distributed training • Computer vision • LLMs or ...

Blend360

Associate Director of Data Science

Columbia, MD · On-site

$58K - $59K/yr

Design and implement AI solutions leveraging advanced techniques, including prompt engineering, agentic architectures, RAG, computer vision, predictive modeling, deep learning, and optimization.

Blend360

Associate Director of Data Science

Columbia, MD · On-site +1

$58K - $59K/yr

Design and implement AI solutions leveraging advanced techniques, including prompt engineering, agentic architectures, RAG, computer vision, predictive modeling, deep learning, and optimization.

Xometry

Senior Machine Learning Engineer

Silver Spring, MD · Hybrid

$108K - $148K/yr

... and applying models at scale using deep learning frameworks like PyTorch or Tensorflow ... We also offer a competitive benefits package, including 401(k) match, medical, dental and vision ...

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All JobsIntern Computer Vision Deep Learning Engineer JobsIntern Computer Vision Deep Learning Engineer Jobs in Baltimore, MD

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 Jun 22, 2026, the average hourly pay for intern computer vision deep learning engineer in Baltimore, MD is $16.93, according to ZipRecruiter salary data. Most workers in this role earn between $14.33 and $19.09 per hour, depending on experience, location, and employer.

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 Baltimore, MD? The most popular types of Computer Vision Deep Learning Engineer jobs in Baltimore, MD are:
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Intern Computer Vision Deep Learning Engineer jobs near you

Machine Learning Engineer

Razor Talent

Columbia, MD

$2.0K/mo

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago

Job description

Machine Learning Engineer

Our clients, a rapidly growing AI-focused software development company supporting federal agencies, is seeking a Machine Learning Engineer.

Delivers mission-critical technology for those who protect what matters. Builds AI-enabled capabilities purpose-built for federal law enforcement and national security partners. Work sits at the intersection of artificial intelligence, cybersecurity, and identity technology. Operates with a startup mentality focused on technical depth, creative problem-solving, and ownership.

Work Location

• McLean, VA or Columbia, MD • Hybrid environment with flexibility for remote work • On-site presence expected 2–3 days per week for team collaboration • Schedule: Monday–Friday; occasional monitoring outside standard hours for extended training jobs

Role Summary

Develop, train, and deploy generative AI models across the full ML lifecycle.

Key Responsibilities

• Train and fine-tune models • Build training pipelines • Develop evaluation frameworks • Optimize inference performance • Integrate models into production • Collaborate with engineering teams • Document models and processes

Required Qualifications

• 3+ years ML engineering • Python + PyTorch • Generative model experience • ML fundamentals • Data pipeline experience • Linux/Docker/AWS familiarity • U.S. citizenship

Preferred Qualifications

• Distributed training • Computer vision • LLMs or RAG • Production ML experience

What Success Looks Like

• 30 days: Learn systems • 90 days: Deliver models • 6 months: Production deployment

Compensation & Benefits

• Fully paid medical, dental, and vision insurance premiums • 10% company contribution to a Vanguard-sponsored 401(k) plan, vested immediately • 7 weeks paid time off, accrued semi-monthly • Life, short-term, and long-term disability insurance • Dependent care and health FSA accounts • $5,000 annual professional development and tuition reimbursement • $200 monthly communication allowance • $2,000 technology allowance every two years • Employee equity plan • Referral, annual, and spot bonuses

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