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Computer Vision Researcher Jobs (NOW HIRING)

SumerSports LLC

Computer Vision Engineer

$114K - $134K/yr

We're hiring a hands-on Computer Vision Engineer to build and improve sports video intelligence ... You'll spend most of your time on CV research + applied modeling (experiments, architectures ...

Norbert Health

Computer Vision/ML Engineer

Brooklyn, NY · On-site

$117K - $138K/yr

Contribute to the architecture and implementation of the computer vision stack from research to production What we look for: * Master's or PhD degree in Machine learning / Computer vision * Strong ...

Norbert Health

Computer Vision/ML Engineer

New York, NY · On-site

$122K - $143K/yr

Contribute to the architecture and implementation of the computer vision stack from research to production What we look for: * Master's or PhD degree in Machine learning / Computer vision * Strong ...

Norbert Health

Computer Vision/ML Engineer

New York, NY · On-site

$122K - $143K/yr

Contribute to the architecture and implementation of the computer vision stack from research to production What we look for: * Master's or PhD degree in Machine learning / Computer vision * Strong ...

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All JobsComputer Vision Researcher Jobs

Computer Vision Researcher information

See salary details

$30K

$113.1K

$164.5K

How much do computer vision researcher jobs pay per year?

As of Jun 19, 2026, the average yearly pay for computer vision researcher in the United States is $113,102.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,000.00 and $154,000.00 per year, depending on experience, location, and employer.

What does a Computer Vision Researcher do?

A Computer Vision Researcher develops algorithms and models that enable computers to interpret and understand visual information from the world, such as images and videos. They work on tasks like object detection, image segmentation, and facial recognition, often using techniques from machine learning and artificial intelligence. Their work is applied in fields such as autonomous vehicles, medical imaging, robotics, and augmented reality. Computer Vision Researchers typically conduct experiments, publish scientific papers, and collaborate with engineers to implement their findings in real-world applications.

What are some common challenges faced by Computer Vision Researchers when transitioning from theoretical research to practical applications?

Computer Vision Researchers often encounter challenges when moving from theoretical models to real-world deployment, such as dealing with noisy or incomplete data, ensuring scalability, and optimizing models for real-time performance. Collaborative work with software engineers and domain experts is crucial to address these issues and to adapt state-of-the-art algorithms for production environments. Additionally, staying updated with rapidly evolving tools and frameworks is essential for successfully bridging the gap between research and application.

What is the difference between Computer Vision Researcher vs Machine Learning Engineer?

AspectComputer Vision ResearcherMachine Learning Engineer
Required CredentialsMaster's or PhD in Computer Science, AI, or related fieldsBachelor's or Master's in Computer Science, Data Science, or related fields
Work EnvironmentResearch labs, academia, R&D departmentsTech companies, startups, product teams
Employer & Industry UsageUniversities, research institutions, AI-focused companiesTechnology firms, software companies, AI product development
Common Search & ComparisonYesYes

While both roles involve AI and machine learning, a Computer Vision Researcher primarily focuses on developing algorithms for visual data analysis and often works in research settings. In contrast, a Machine Learning Engineer applies machine learning techniques to build scalable AI products and solutions in industry environments.

What are the key skills and qualifications needed to thrive as a Computer Vision Researcher, and why are they important?

To thrive as a Computer Vision Researcher, you need a strong background in mathematics, machine learning, image processing, and typically a graduate degree in computer science or a related field. Experience with deep learning frameworks (such as TensorFlow or PyTorch), programming languages (like Python or C++), and familiarity with relevant research publications are highly valued. Creativity, problem-solving abilities, and strong communication skills help researchers innovate and effectively share findings. These competencies are vital for advancing technology, developing novel algorithms, and collaborating within multidisciplinary teams.
More about Computer Vision Researcher jobs
What states have the most Computer Vision Researcher jobs? States with the most job openings for Computer Vision Researcher jobs include:
What job categories do people searching Computer Vision Researcher jobs look for? The top searched job categories for Computer Vision Researcher jobs are:
Computer Vision Researcher jobs near you
Infographic showing various Computer Vision Researcher job openings in the United States as of June 2026, with employment types broken down into 25% Internship, 50% Full Time, and 25% Temporary. Highlights an 100% In-person job distribution, with an average salary of $113,102 per year, or $54.4 per hour.
Machine Learning Computer Vision Intern

Machine Learning Computer Vision Intern

Syntiant

Redwood City, CA

Temporary

Posted 16 days ago

Job description

Summary Description:

Syntiant Corp., a leader in the high-growth AI software and semiconductor solutions space, is looking for a Machine Learning Computer Vision Intern expand our computer vision detection capabilities through strategic framework diversification and cutting-edge algorithm exploration.

We have a robust, production-proven detection pipeline implemented in C++ that consistently delivers high-quality results in our live systems. To accelerate our research initiatives and explore next-generation detection methodologies, we're creating a parallel PyTorch-based research pipeline. This exciting initiative will enable our team to rapidly prototype and validate innovative detection approaches while maintaining our proven production standards.

PyTorch is the industry-leading framework for computer vision research and experimentation. By leveraging PyTorch's rich ecosystem and flexibility, this project will unlock opportunities to integrate state-of-the-art detection architectures and explore novel approaches that could define the future of our detection capabilities.

This internship offers the unique opportunity to work with both production-grade systems and cutting-edge research, directly shaping the future of our computer vision capabilities while gaining invaluable experience in both software engineering and AI research.

Requirements

Specific Duties and Responsibilities:

  • Architecting a PyTorch-based detection pipeline inspired by our proven C++ system.
  • Implementing and validating detection algorithms using modern deep learning frameworks.
  • Ensuring seamless integration and output consistency across platforms.
  • Experimenting with cutting-edge detection architectures (YOLO, R-CNN variants, Transformers).
  • Pioneering detection improvements and performance optimizations.
  • Contributing to our research roadmap with innovative detection methodologies.
  • Documenting breakthrough findings and technical recommendations.

Qualifications, Education, and Experience Required:

  • Candidate pursuing a Bachelor's or Master's degree in Computer Science, Computer Engineering, or related field with hands-on experience in computer vision and PyTorch.
  • Industry work experience is not required, but it would be good to have.

Benefits

About Syntiant:

Founded in 2017 and headquartered in Irvine, Calif., Syntiant Corp. is a leader in delivering hardware and software solutions for edge AI deployment. The company's purpose-built silicon and hardware-agnostic models are being deployed globally to power edge AI speech, audio, sensor and vision applications across a wide range of consumer and industrial use cases, from earbuds to automobiles. Syntiant's advanced chip solutions merge deep learning with semiconductor design to produce ultra-low-power, high performance, deep neural network processors. Syntiant also provides compute-efficient software solutions with proprietary model architectures that enable world-leading inference speed and minimized memory footprint across a broad range of processors. The company is backed by several of the world's leading strategic and financial investors including Intel Capital, Microsoft's M12, Applied Ventures, Bosch Ventures, the Amazon Alexa Fund, and Atlantic Bridge Capital. More information on the company can be found by visiting www.syntiant.com.

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