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Entry Level Computer Vision Engineer Jobs (NOW HIRING)

Skilled in at least one programming language used in Computer Vision (e.g. Python and/or C++) Preferred Qualifications: * Experience with common AI/ML tools and frameworks such as PyTorch, PyTorch ...

Senior Computer Vision Engineer

Santa Clara, CA · On-site

$143K - $189K/yr

We are seeking a talented Computer Vision / Machine Learning Engineer to join our global team. In this role, you will develop and optimize multi-modal models and computer vision systems, driving ...

Senior Computer Vision Engineer

Santa Clara, CA · On-site

$143K - $189K/yr

We are seeking a talented Computer Vision / Machine Learning Engineer to join our global team. In this role, you will develop and optimize multi-modal models and computer vision systems, driving ...

We are seeking an Intermediate Computer Vision R&D Engineer to join our team. The candidate will be part of the core team of computer vision engineers. We will be developing new product lines ...

Experience with 3D Vision * Publication record in relevant venues (CVPR, ICLR, ICCV, ECCV, NeurIPS, AAAI, SIGGRAPH) $19 - $65 an hour Our internship hourly rates are a standard pay determined based ...

Experience with 3D Vision * Publication record in relevant venues (CVPR, ICLR, ICCV, ECCV, NeurIPS, AAAI, SIGGRAPH) $19 - $65 an hour Our internship hourly rates are a standard pay determined based ...

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Entry Level Computer Vision Engineer information

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$48.5K

$121.5K

$137.5K

How much do entry level computer vision engineer jobs pay per year?

As of Jun 9, 2026, the average yearly pay for entry level computer vision engineer in the United States is $121,515.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,500.00 and $131,500.00 per year, depending on experience, location, and employer.

What does an Entry Level Computer Vision Engineer do?

An Entry Level Computer Vision Engineer assists in developing computer systems that can interpret and process visual information from the world, such as images and videos. They typically work with machine learning algorithms, neural networks, and image processing techniques to solve problems like object detection, facial recognition, and image classification. Their work often involves data annotation, model training, testing, and optimizing algorithms under the guidance of senior engineers. Entry level engineers usually have a background in computer science or related fields and are familiar with programming languages such as Python and libraries like OpenCV and TensorFlow.

What is the difference between Entry Level Computer Vision Engineer vs Computer Vision Analyst?

AspectEntry Level Computer Vision EngineerComputer Vision Analyst
Required CredentialsBachelor's in CS, Electrical Engineering, or related; knowledge of ML and CV frameworksBachelor's in CS, Data Science, or related; strong analytical skills
Work EnvironmentTech companies, R&D labs, startups; focus on developing algorithms and modelsData analysis teams, research firms; focus on interpreting CV data and insights
Employer & Industry UsageTech, automotive, robotics, healthcareMarket research, consulting, security, and surveillance

Entry Level Computer Vision Engineers focus on developing and implementing computer vision algorithms, often working in R&D or product teams. In contrast, Computer Vision Analysts primarily interpret and analyze CV data to generate insights. Both roles require a strong technical background, but their daily tasks and industry applications differ.

What types of projects do entry level computer vision engineers typically work on, and how much collaboration is involved?

Entry level computer vision engineers often work on tasks like annotating datasets, developing and testing algorithms for image or video analysis, and supporting the integration of computer vision models into existing applications. These projects usually require close collaboration with data scientists, senior engineers, and sometimes product managers to ensure models meet performance requirements. It's common to participate in code reviews and team meetings, fostering a supportive learning environment. As you gain experience, you'll likely take on more complex responsibilities and contribute to larger project components.

What are the key skills and qualifications needed to thrive as an Entry Level Computer Vision Engineer, and why are they important?

To thrive as an Entry Level Computer Vision Engineer, you need a solid background in computer science, mathematics, and image processing, often supported by a relevant degree. Familiarity with programming languages like Python or C++, experience with deep learning frameworks (such as TensorFlow or PyTorch), and knowledge of OpenCV are typically required. Strong problem-solving abilities, attention to detail, and effective teamwork set top candidates apart. These skills and tools are essential for developing, optimizing, and implementing computer vision solutions in real-world applications.
More about Entry Level Computer Vision Engineer jobs
What cities are hiring for Entry Level Computer Vision Engineer jobs? Cities with the most Entry Level Computer Vision Engineer job openings:
What are the most commonly searched types of Computer Vision Engineer jobs? The most popular types of Computer Vision Engineer jobs are:
What states have the most Entry Level Computer Vision Engineer jobs? States with the most job openings for Entry Level Computer Vision Engineer jobs include:
Infographic showing various Entry Level Computer Vision Engineer job openings in the United States as of May 2026, with employment types broken down into 92% Full Time, 3% Part Time, and 5% Contract. Highlights an 92% In-person, 3% Hybrid, and 5% Remote job distribution, with an average salary of $121,515 per year, or $58.4 per hour.
Senior Computer Vision Engineer

Senior Computer Vision Engineer

Stryker

Menlo Park, CA • On-site

$116K - $193K/yr

Full-time

Posted 13 days ago


Job description

Work Flexibility: Hybrid
What You Will Do:
Lead the development and optimization of state-of-the-art computer vision and Artificial Intelligence / machine learning (AI/ML) algorithms and models from conceptualization to deployment on both edge and cloud platforms. Conduct rigorous performance analysis to systematically improve the functionality of computer vision and AI/ML techniques within our product suite. Manage the entire lifecycle of data handling for machine learning models, ensuring compliance with privacy standards during data collection, processing, and labeling. Ensure the reliability and robustness of computer vision and machine learning applications under diverse operational conditions.
  • Independently design, prototype, evaluate, optimize, implement and deploy computer vision and AI/ML algorithms as an integral part of AI-powered medical devices and technologies
  • Be an expert in applying core machine learning techniques including deep learning, feature extraction, model training, evaluation and deployment to design and develop AI-powered medical devices.
  • Skilled in quickly identifying key advances in the computer vision and AI/ML literature and relevance to problems being solved as well as explaining and justifying usage of new approaches through prototyping and demonstration
  • Design and develop novel computer vision and/or machine learning algorithms in areas such as: real-time scene and object tracking (e.g. face tracking, body tracking, key point estimation), depth sensing, 3D stereo and volumetric reconstruction, 2D / 3D medical imaging segmentation, deriving biomarkers from medical imaging such as CT scans, X-Ray, MRI, etc.
  • Collaborate with internal or external teams in acquiring, storing, organizing, annotating, versioning and processing large amounts of data needed for training computer vision and machine learning models
  • Design algorithm evaluation frameworks, schedule and report algorithm, AI/ML model, and system performance regularly.
  • Document and present progress in algorithm design, development, and evaluation (requirements/design/architecture/bugs/tests).

What You Will Need:
Required Qualifications:
  • Bachelor's Degree in Computer Science, Machine Learning, Artificial Intelligence, Electrical Engineering, Mathematics, Statistics, or related field AND 2 years of industry experience
  • OR Master's/PhD Degree in Computer Science, Machine Learning, Artificial Intelligence, Electrical Engineering, Mathematics, Statistics
  • Strong understanding of medical imaging modalities such as CT, MRI, X-ray, ultrasound, fluoroscopy, angiography or endoscopy, including common artifacts, acquisition variability, and clinical workflow constraints
  • Experience with medical imaging data formats and standards, including DICOM, NIfTI, PACS workflows, metadata handling, and image anonymization
  • Skilled in at least one programming language used in Computer Vision (e.g. Python and/or C++)

Preferred Qualifications:
  • Experience with common AI/ML tools and frameworks such as PyTorch, PyTorch-Lightning, Tensorflow/keras, OpenCV, pandas, scikit-learn, MLFlow, ONNX, cloud (one of AWS/GCP/Azure), docker container.
  • Experience in designing and training and deploying production-grade deep learning architectures for computer vision applications with a broad under-standing of latest CV / DL methods and literature.

  • $116,100 - $193,400 USD Annual

Travel Percentage: 10%
Stryker Corporation is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, gender identity, sexual orientation, national origin, disability, or protected veteran status. Stryker is an EO employer - M/F/Veteran/Disability.
Stryker Corporation will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information.