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Computer Vision Machine Learning Jobs in California

Steg.AI

Machine Learning Scientist

Irvine, CA · On-site

$140 - $200/hr

Our machine learning team currently consists of 3 PhDs in Computer Vision.We are looking for a highly motivated machine learning scientist with a passion for groundbreaking AI technology for ...

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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 are popular job titles related to Computer Vision Machine Learning jobs in California?

For Computer Vision Machine Learning jobs in California, the most frequently searched job titles are:

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:

Computer Vision Machine Learning jobs near you
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.

Senior Computer Vision & Machine Learning Engineer

Voiceflow

Palo Alto, CA • On-site

$120 - $160/hr

Other

Posted 3 days ago

New

Job description

Job Description

Buzz is revolutionizing the analytics and maintenance of power grid infrastructure through our advanced AI solutions. Our computer vision systems analyze critical infrastructure to enhance safety, reliability, and operational efficiency across the power grid network. We're seeking an experienced Machine Learning Engineer to help lead our computer vision initiatives. You'll drive the development of cutting-edge models for power grid analysis and provide a leadership anchor on a team of talented ML engineers.

Responsibilities
  • Architect and lead end-to-end computer vision projects focused on: Equipment defect detection, Thermal anomaly identification, Vegetation encroachment monitoring, Surveillance of closed areas for human and animal intrusions
  • Drive innovation by incorporating the latest advances in deep learning and generative AI to enhance model training, accuracy and reliability
  • Develop production-grade Python libraries for the complete ML lifecycle
  • Mentor team members and establish best practices for model development, evaluation, deployment, and monitoring
  • Advocate for and uphold software quality standards within the ML team
Qualifications & Experience
  • 7-10 years of industry experience in computer vision and machine learning
  • Deep expertise in modern computer vision and deep neural networks including: Object detection, Semantic segmentation, Image classification, Similarity search, Vision language models
  • Proven track record of deploying and maintaining ML models in production
  • Expert proficiency in PyTorch, Lightning, OpenCV, and Scikit-Learn
  • Proficiency in FastAPI and Pydantic
  • Strong software engineering foundation including: Git version control, Test driven development (Pytest), CI/CD, ML devops, Python type hinting
  • 2-3 years of proven leadership experience of technical teams
Desired Additional Experience
  • Multi-modal computer vision
  • Custom object detection model development
  • Generative models for data augmentation
  • ML deployment on edge devices
  • Extracting measurements from GIS and/or drone metadata enriched imagery
  • Model quantization
  • Systematic hyperparameter tuning
Additional information
  • This position does not include sponsorship for United States work authorization.
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