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Data Annotation Jobs in Irvine, CA (NOW HIRING)

FieldAI

2.53 3D Machine Learning Engineer

Irvine, CA · On-site

... data annotation strategies and ensure high model performance and generalization. Qualifications : Required : • Bachelor's or Master's degree in Computer Science, Machine Learning, Robotics, or a ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

$150K - $200K/yr

Work closely with the labeling and data operations teams to define robust data annotation strategies and ensure high model performance and generalization. What You Have * Bachelor's or Master ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

$150K - $200K/yr

Work closely with the labeling and data operations teams to define robust data annotation strategies and ensure high model performance and generalization. What You Have * Bachelor's or Master ...

FieldAI

3D Machine Learning Engineer

Irvine, CA · On-site

$150K - $200K/yr

Work closely with the labeling and data operations teams to define robust data annotation strategies and ensure high model performance and generalization. What You Have * Bachelor's or Master ...

Fallbrook Public Utility District

SCADA Analyst - CPEN

CA · On-site

$132K - $165K/yr

Generates reports and data runs; * Develops scripts to automate repetitive tasks, for data ... annotation used for troubleshooting are kept updated; * Designs, programs, maintains, and upgrades ...

All JobsData Annotation JobsData Annotation Jobs in Irvine, CA

Data Annotation information

See Irvine, CA salary details

$9

$26

$56

How much do data annotation jobs pay per hour?

As of Jul 31, 2026, the average hourly pay for data annotation in Irvine, CA is $26.32, according to ZipRecruiter salary data. Most workers in this role earn between $17.80 and $31.34 per hour, depending on experience, location, and employer.

What does a typical workday look like for someone in a Data Annotation role?

A typical workday as a Data Annotator involves reviewing datasets—such as images, audio, text, or video—and accurately labeling or categorizing information according to specific project guidelines. Most Data Annotators work independently, but they often collaborate with project managers or data scientists to clarify requirements and resolve ambiguities. Tasks may be repetitive, but adhering to precise standards is vital for maintaining data quality. Work environments can range from technology companies to remote or freelance settings, and advancement opportunities exist as team leads or quality assurance specialists for those who excel in consistency and reliability.

Is data annotation a genuine job?

Data annotation is a legitimate job that involves labeling data such as images, text, or audio to help train machine learning models. It often requires attention to detail and familiarity with annotation tools, and can be found in various industries like technology and healthcare.

Does data annotation pay well?

Data annotation jobs typically offer entry-level pay that varies depending on the employer, location, and complexity of the tasks. While some positions pay hourly wages comparable to other administrative or clerical roles, experienced annotators working on specialized projects or with advanced tools can earn higher rates. Overall, data annotation is often considered an entry-level position with moderate pay potential.

What is a Data Annotation job?

A Data Annotation job involves labeling and categorizing data, such as text, images, audio, or video, to help train machine learning models. Annotators apply tags, bounding boxes, or classifications to data based on specific guidelines. This process improves the accuracy of AI systems in recognizing patterns and making predictions. Many data annotation jobs require attention to detail and familiarity with specific domains. It is commonly used in applications like autonomous driving, natural language processing, and computer vision.

How hard is it to get hired by data annotation?

Getting hired for a data annotation role generally requires basic computer skills, attention to detail, and sometimes familiarity with specific tools or platforms. Many positions are entry-level and do not require advanced education, making the hiring process relatively accessible, though competition can vary based on the employer and location.

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

To thrive in Data Annotation, you need strong attention to detail, accuracy, and basic data handling skills, often supported by a high school diploma or equivalent. Familiarity with annotation platforms, data labeling software, or content management systems is frequently required, though specific certifications are rare. Excellent communication, time management, and the ability to focus on repetitive tasks distinguish top performers in this role. These skills are crucial because accurate and consistent data annotation directly impacts the quality of machine learning models and AI applications.

What does a data annotator do?

A data annotator labels and tags data such as images, text, or videos to help machine learning models understand and learn from the data. They use tools and follow guidelines to ensure accuracy and consistency, often working with large datasets in a structured environment. Attention to detail and knowledge of annotation tools are important for this role.
What are the most commonly searched types of Data Annotation jobs in Irvine, CA? The most popular types of Data Annotation jobs in Irvine, CA are:
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What job categories do people searching Data Annotation jobs in Irvine, CA look for? The top searched job categories for Data Annotation jobs in Irvine, CA are:
What cities near Irvine, CA are hiring for Data Annotation jobs? Cities near Irvine, CA with the most Data Annotation job openings:
Data Annotation jobs near you
Infographic showing various Data Annotation job openings in Irvine, CA as of July 2026, with employment types broken down into 2% Locum Tenens, 34% Full Time, 26% Part Time, 1% Contract, 36% Nights, and 1% Summer. Highlights an 56% Physical, 1% Hybrid, and 43% Remote job distribution, with an average salary of $54,745 per year, or $26.3 per hour.

2.53 3D Machine Learning Engineer

FieldAI

Irvine, CA • On-site

Full-time

Re-posted 20 days ago

Job description

Job Summary:
FieldAI is a company based in Irvine, California, specializing in embodied AI and robotics. They are seeking a 3D Machine Learning Engineer to design, implement, and maintain advanced 3D machine learning models for processing reality capture data, contributing to automated progress tracking and scene understanding in construction environments.
Responsibilities:
• Design and implement scalable machine learning pipelines for large-scale 3D spatial data processing for point cloud analysis, object detection, segmentation, and scene understanding.
• Train, optimize, and deploy deep learning models using PyTorch, TensorFlow, or equivalent frameworks on cloud platforms such as AWS (e.g., SageMaker, EC2).
• Collaborate with software and systems engineers to integrate models into production environments and continuously improve inference pipelines.
• Analyze diverse sensor inputs, including RGBD imagery, LiDAR point clouds, 360 photos, audio, and Building Information Models (BIM).
• Work closely with the labeling and data operations teams to define robust data annotation strategies and ensure high model performance and generalization.
Qualifications:
Required:
• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Robotics, or a related technical field.
• 2+ years of hands-on industry experience developing and deploying machine learning systems for 3D point clouds, perception, or spatial understanding tasks.
• Strong background in 3D machine learning, with experience in deep learning for point clouds, multi-view fusion, or geometric learning.
• Strong expertise in Python and deep learning frameworks: PyTorch, TensorFlow, or similar.
• Familiarity with OpenCV and PCL (Point Cloud Library) for classical computer vision and 3D data preprocessing.
• Experience training, evaluating, and deploying ML models using cloud infrastructure (e.g., AWS, SageMaker) and containerized workflows.
• Solid understanding of the end-to-end ML lifecycle, including experiment tracking, reproducibility, model versioning, and optimization for production.
• Proven ability to work in fast-paced, interdisciplinary teams across software, ML, and product teams.
Preferred:
• Experience working with BIM data, digital twins, or construction-related sensor data.
• Background in geometric deep learning, 3D mesh analysis, GIS systems, or structured scene representations.
• Familiar with MLOps pipelines using Ray, SageMaker, MLflow, or Kubeflow.
• Strong foundation in geometric computer vision, robotics, or algorithmic 3D reasoning.
• Exposure to graph neural networks, geodesic computations, or neural implicit representations (e.g., NeRF, Occupancy Networks).
• Deep experience with point cloud and graph learning frameworks such as Open3D-ML, Torch-Points3D, PyG, or MMDetection3D.
• Experience building custom modules for SparseConvNet or 3D transformers.
Company:
FieldAI is building general robot intelligence for the physical world. Founded in 2023, the company is headquartered in Mission Viejo, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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