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Image Labeling Jobs in California (NOW HIRING)

$170K - $201K/yr

... image. Provides a high level of product expertise and customer service to all accounts. Calls on customers (academic & community setting) in a specific geography, provides on-label technical and ...

Oncology Account Manager

Sacramento, CA · On-site

$170K - $201K/yr

... image. * Provides a high level of product expertise and customer service to all accounts. * Calls on customers (academic & community setting) in a specific geography, provides on-label technical and ...

... image. * Provides a high level of product expertise and customer service to all accounts. * Calls on customers (academic & community setting) in a specific geography, provides on-label technical and ...

... labeling of reusable items; assisting in facilitating the daily surgery schedule; intake of ... image representing O.R. service to patients and personnel. · Must file an incident report for any ...

... label ventures. Since 2000, in addition to operating our own slate of brands, we have been ... Perform color correction, skin retouching, wrinkle reduction, background cleanup/removal, and image ...

Data Quality Manager

San Jose, CA · On-site

$140K - $200K/yr

The standards, tooling, and methodologies that worked for prior generations of AI, image ... This is not a labeling-team management role. We're looking for a strategic operator and thought ...

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Image Labeling information

See California salary details

$10

$13

$16

How much do image labeling jobs pay per hour?

As of Jun 10, 2026, the average hourly pay for image labeling in California is $13.78, according to ZipRecruiter salary data. Most workers in this role earn between $12.36 and $15.19 per hour, depending on experience, location, and employer.

What jobs make $3,000 a month without a degree?

In the field of image labeling, experienced freelancers or contractors can earn around $3,000 per month by completing large volumes of labeling tasks for AI training datasets. Success depends on skills, efficiency, and the platform used, with some roles offering flexible schedules and minimal formal education requirements.

What does a typical workday look like for someone in an Image Labeling position?

A typical day as an Image Labeler involves reviewing a high volume of images and accurately applying tags, annotations, or classifications according to specific project guidelines. You may work individually or as part of a larger data annotation team, often collaborating with project managers or quality assurance specialists to ensure consistency and accuracy. The work is generally computer-based and can often be performed remotely. Challenges may include meeting tight deadlines and adapting to varying project standards, but the role also offers opportunities to develop skills valuable in the broader artificial intelligence and data science fields.

What is an Image Labeling job?

An Image Labeling job involves annotating or tagging images with relevant labels to help train machine learning models. This can include identifying objects, bounding boxes, classifications, or segmenting specific areas within an image. The labeled data is crucial for AI systems to recognize patterns and make accurate predictions. It is commonly used in industries like autonomous driving, healthcare, and e-commerce. No specialized degree is usually required, but attention to detail and accuracy are important.

What are the key skills and qualifications needed to thrive in the Image Labeling position, and why are they important?

To excel in Image Labeling, candidates should have high attention to detail, basic computer proficiency, and familiarity with digital image formats. Experience with data annotation tools and platforms such as Labelbox or Supervisely is often preferred, though formal certifications are not always required. Strong organizational skills, focus, and the ability to work both independently and as part of a team are valuable soft skills in this role. These qualifications help ensure consistently accurate labeling, which is essential for building high-quality machine learning datasets.

What are the most commonly searched types of Image Labeling jobs in California? The most popular types of Image Labeling jobs in California are:
What job categories do people searching Image Labeling jobs in California look for? The top searched job categories for Image Labeling jobs in California are:
What cities in California are hiring for Image Labeling jobs? Cities in California with the most Image Labeling job openings:
Infographic showing various Image Labeling job openings in California as of June 2026, with employment types broken down into 76% Full Time, 13% Part Time, 2% Temporary, and 9% Contract. Highlights an 93% In-person, and 7% Remote job distribution, with an average salary of $28,672 per year, or $13.8 per hour.
Machine Learning Engineer - Generative AI

Machine Learning Engineer - Generative AI

Dream Technologies Inc

San Francisco, CA • On-site

Full-time

Posted 26 days ago


Job description

We are looking for a Generative AI engineer to work on the full lifecycle of novel spatial generative AI model development, defining the correct frame of an inference problem, structuring image-based training data into usable formats, training and testing models, deploying performant systems into our production architecture stack.
Upcoming Challenges
  • Generate high quality renovation and home design layouts using state-of-the-art generative models.
  • Build a model that adapts to user feedback and suggests home design tailored to user preferences.
  • Define required datasets and work with labeling agencies to generate high quality data.
  • Deploy models to production environments and iterate with real users on real-world problems.

What we Require
  • MS in Computer Science with a focus or specialty in Machine Learning
  • 2+ Years of experience training and deploying real-world AI . Deep understanding of model architectures, training pipelines, and evaluation methodologies.
  • Creativity and technical depth to explore, evaluate, and iterate on different machine learning approaches
  • Scrappiness and speed in getting models built and tested under real-world constraints.
  • Strong background in algorithms, data structures, and mathematics, with the ability to design performant solutions to spatial and generative problems.
  • Proficiency in Python, with a strong preference for experience using NumPy and PyTorch.