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Computer Vision Engineer Jobs in California (NOW HIRING)

Dexterity

Senior Computer Vision Engineer

Redwood City, CA · On-site

$160K - $200K/yr

In this role at Dexterity, you will be working on writing Computer Vision code and building Machine Learning models for computer vision. The role will involve understanding our current systems and ...

Cesna Group

Computer Vision R&D Engineer

San Diego, CA · On-site

$100K - $200K/yr

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 ...

PlusAI

Computer Vision Engineer Intern

Santa Clara, CA · On-site

$19 - $65/hr

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 ...

Brachium

Robotics Vision Engineer

San Ramon, CA

- Robotics Vision Engineer Title Robotics Vision Engineer Company Description We are a 3-year-old ... Develop and evaluate state-of-the-art computer vision algorithms for real-time control of robots ...

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$47.9K

$119.9K

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How much do computer vision engineer jobs pay per year?

As of Jul 7, 2026, the average yearly pay for computer vision engineer in California is $119,924.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,000.00 and $129,800.00 per year, depending on experience, location, and employer.

What do computer vision engineers do?

Computer vision engineers develop algorithms and models that enable computers to interpret and analyze visual data such as images and videos. They often work with machine learning frameworks, programming languages like Python or C++, and tools such as OpenCV or TensorFlow to create applications in areas like object detection, facial recognition, and autonomous systems.

What engineers make $300,000 a year?

Senior computer vision engineers, especially those with advanced skills in deep learning, machine learning, and experience with tools like TensorFlow or PyTorch, can earn $300,000 or more annually in high-demand industries such as technology, autonomous vehicles, or AI research. Compensation often depends on experience, location, and company size, with some roles in Silicon Valley or major tech firms reaching this level through base salary, bonuses, and stock options.

What are Computer Vision Engineers?

Computer Vision Engineers are professionals who develop algorithms and systems that enable computers to interpret and process visual information from the world, such as images and videos. They work on tasks like object detection, facial recognition, image segmentation, and more, often using machine learning and deep learning techniques. These engineers apply their expertise in fields like robotics, autonomous vehicles, healthcare, and augmented reality, turning raw visual data into actionable insights.

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

AspectComputer Vision EngineerMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, Electrical Engineering, or related; knowledge of image processing and computer vision librariesBachelor's or Master's in CS, Data Science, or related; strong programming and statistical skills
Work EnvironmentDevelops algorithms for image/video analysis, object detection, and recognition in tech, automotive, or healthcare industriesBuilds models for various data types, including text, images, and structured data across multiple sectors
Employer & Industry UsageTech companies, autonomous vehicles, robotics, healthcareTech firms, finance, e-commerce, healthcare, and research institutions

While both roles involve machine learning techniques, Computer Vision Engineers specialize in developing algorithms for visual data, whereas Machine Learning Engineers work on broader data modeling across various data types. The roles often overlap but differ mainly in focus and application areas.

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

To thrive as a Computer Vision Engineer, you need a strong background in computer science, mathematics, and machine learning, often supported by a relevant degree and experience with image processing algorithms. Familiarity with tools and frameworks such as OpenCV, TensorFlow, PyTorch, and proficiency in programming languages like Python or C++ is essential, along with knowledge of deep learning techniques. Analytical thinking, creativity, and effective communication are standout soft skills for this role. These skills and qualities are crucial for developing innovative vision solutions, interpreting complex data, and collaborating efficiently within interdisciplinary teams.

What engineer makes $500,000 a year?

A senior computer vision engineer at top tech companies or in specialized industries can earn $500,000 or more annually, often including bonuses and stock options. These roles typically require advanced skills in machine learning, deep learning, and experience with tools like TensorFlow or PyTorch, along with a strong educational background and years of experience. Compensation varies based on location, company size, and individual expertise.

What Does a Computer Vision Engineer Do?

Computer vision is a branch of artificial intelligence that attempts to replicate human analytical processes by using algorithms and computer models to understand and identify patterns in images. As a computer vision engineer, you use software to handle the processing and analysis of large data populations, and your efforts support the automation of predictive decision-making efforts. Your responsibilities involve research, programming, data analysis, and user interface design. You may work on a variety of exciting development projects like self-driving cars, mobile devices, innovative features and capabilities in sports and entertainment, and the next generation of social media enhancements.

What are some common challenges faced by Computer Vision Engineers when deploying models to production environments?

Computer Vision Engineers often encounter challenges such as ensuring model accuracy in diverse real-world conditions, optimizing models for efficiency on edge devices, and handling large-scale data processing. Deploying models to production requires balancing performance with resource constraints and addressing issues like latency, scalability, and data privacy. Collaborating closely with software engineers and data scientists is crucial to integrate solutions effectively and continuously monitor and improve model performance in live applications.

Will AI replace computer vision engineers?

AI is transforming the field of computer vision, but computer vision engineers are essential for developing, training, and maintaining AI models and systems. Their expertise in algorithms, programming, and domain knowledge ensures the effective application of AI in real-world scenarios, making complete replacement unlikely in the near term.
More about Computer Vision Engineer jobs
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What are popular job titles related to Computer Vision Engineer jobs in California? For Computer Vision Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Computer Vision Engineer jobs in California look for? The top searched job categories for Computer Vision Engineer jobs in California are:
What cities in California are hiring for Computer Vision Engineer jobs? Cities in California with the most Computer Vision Engineer job openings:
Computer Vision Engineer jobs near you

Computer Vision Specialist (Robotics)

Hyphen Connect Limited

San Francisco, CA • On-site

Full-time

Re-posted 15 days ago

Job description

We are seeking a skilled Computer Vision Engineer. This role is pivotal in advancing robotic systems through high-fidelity spatial mapping and real-time object recognition. You will work closely with cutting-edge technology to integrate vision systems with robotic manipulation and navigation, to enhance automation capabilities.
Responsibilities:
  • Implement high-fidelity spatial mapping and real-time object recognition pipelines.
  • Integrate vision systems directly with robotic manipulation and navigation controls.
  • Train and fine-tune Vision-Language-Action (VLA) models.

Required Skills:
  • Proficiency in 3D Gaussian Splatting, NeRFs, and modern SLAM algorithms.
  • Experience with multimodal spatial AI frameworks.
  • Previous work integrating computer vision outputs with ROS2 or robotic hardware.

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