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Computer Vision Machine Learning Jobs in California

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Computer Vision Machine Learning information

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$12

$19

$29

How much do computer vision machine learning jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for computer vision machine learning in California is $19.66, according to ZipRecruiter salary data. Most workers in this role earn between $16.15 and $21.59 per hour, depending on experience, location, and employer.

What is a computer vision machine learning engineer?

A Computer Vision Machine Learning Engineer is a professional who develops algorithms and models that enable computers to interpret and understand visual data from the world, such as images and videos. They use techniques from machine learning, deep learning, and image processing to build systems capable of tasks like object detection, image classification, facial recognition, and scene understanding. Their work is critical in fields such as autonomous vehicles, healthcare imaging, security, and augmented reality. These engineers typically have strong skills in programming, mathematics, and data analysis, and often work closely with data scientists and software developers.

What are the key skills and qualifications needed to thrive as a computer vision machine learning engineer?

To thrive as a Computer Vision Machine Learning Engineer, you need strong foundations in mathematics, programming (especially Python or C++), and expertise in machine learning algorithms, typically supported by a degree in computer science, engineering, or a related field. Familiarity with deep learning frameworks like TensorFlow or PyTorch and experience with image processing libraries are essential, along with knowledge of version control systems. Strong problem-solving, collaboration, and communication skills help you translate complex requirements into effective models and work efficiently in multidisciplinary teams. These skills ensure the development of robust computer vision solutions that address real-world challenges and drive innovation.

What are some common challenges faced by computer vision machine learning engineers when deploying models to production environments?

Computer Vision Machine Learning engineers often encounter challenges such as ensuring models perform well on real-world, diverse image data that may differ from training datasets. Managing computational efficiency and latency is crucial, especially for real-time applications. Additionally, integrating models with existing software systems and maintaining accuracy as data evolves can be complex. Collaboration with data engineers, software developers, and product teams is essential to address these challenges and ensure smooth deployment and monitoring.

What is the difference between Computer Vision Machine Learning vs Data Scientist?

AspectComputer Vision Machine LearningData Scientist
Required CredentialsBachelor's or higher in CS, ML, or related; experience with ML frameworksBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentResearch labs, tech companies, AI startups focusing on visual dataBusiness, finance, healthcare sectors analyzing diverse data sets
Industry UsageDeveloping visual recognition systems, image processingData analysis, predictive modeling, business insights
Common Search/ComparisonYesYes

While both roles involve machine learning, Computer Vision Machine Learning specializes in visual data and image processing, whereas Data Scientists work with a broader range of data types to generate insights across various industries.

Is machine learning used in computer vision?

Yes, machine learning is fundamental to computer vision, enabling systems to interpret and analyze visual data such as images and videos. Computer vision professionals often use techniques like deep learning and neural networks to develop applications like object detection, facial recognition, and image classification.

What job categories do people searching Computer Vision Machine Learning jobs in California look for?

The top searched job categories for Computer Vision Machine Learning jobs in California are:

What cities in California are hiring for Computer Vision Machine Learning jobs?

Cities in California with the most Computer Vision Machine Learning job openings:

Infographic showing various Computer Vision Machine Learning job openings in California as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 13% Part Time, and 5% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $40,886 per year, or $19.7 per hour.

Machine Learning Data Collection Specialist

Prolim Global

Burlingame, CA โ€ข On-site

Contractor

Re-posted 19 hours ago


Job description

PROLIM Global Corporation (www.prolim.com) is currently seeking Machine Learning Data Collection Specialist for location Burlingame, California, United States for one of our Top clients

Job Description:

  • 3 + year of experience in either Software or Data Analytics related fields, with experience of using Linux/Android command console, using Python for data analysis. Basic understanding of Computer Vision/Machine learning is preferred but not required.
  • Either Bachelor's degree in STEM fields, or 3+ years industry/academic experience in developing Python software products or Data Analytics, alternatively 1+ year industry/academic experience in Computer Vision/Machine Learning
  • Experience with these Python analytics libraries: Pandas, Numpy, Plotly

Apply online for immediate consideration, please send your updated resume, and contact info via email praful.salunkey@prolim.com

About PROLIM Corporation  

PROLIM is a leading provider of end-to-end IT, PLM and Engineering Services and Solutions for Global 1000 companies. They understand business as much as technology, and help their customers improve their profitability and efficiency by providing high value technology consulting, staffing, and project management outsourcing services. 

Their IT and PLM consulting offerings include; Advisory, PLM Software/Services, Program Management, Solution Architecture Training/Staffing, Cloud Solutions, Servers/Networking, Infrastructure, ERP Practices and QA Services. Engineering services include Data Translation, CAD/CAM/CAE, Process & Product Engineering, Prototyping, and Testing/Validation within a wide range of markets and industries.