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Entry Level Ai Data Trainer Jobs in California (NOW HIRING)

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Entry Level Ai Data Trainer information

What does an entry level AI data trainer do?

An Entry Level AI Data Trainer is responsible for preparing, labeling, and organizing data that is used to train artificial intelligence models. This involves tasks such as categorizing images, annotating text, and ensuring that data is accurate and relevant for machine learning algorithms. They work closely with data scientists and engineers to improve the quality of AI systems by providing clean and well-labeled datasets. The role is a great way to start a career in artificial intelligence, as it offers hands-on experience with data and insights into how AI models are developed.

What are the key skills and qualifications needed to thrive as an entry level AI data trainer?

To thrive as an Entry Level AI Data Trainer, you need strong analytical skills, attention to detail, and a foundational understanding of data annotation processes, often supported by a bachelor's degree in a related field. Familiarity with data labeling tools, content management systems, and basic programming or scripting (such as Python) is typically required. Excellent communication, teamwork, and adaptability help you effectively interpret guidelines and collaborate with cross-functional teams. These skills ensure high-quality data preparation, which is essential for developing accurate and reliable AI models.

What types of tasks and collaboration can I expect as an entry level AI data trainer?

As an Entry Level AI Data Trainer, you will primarily be responsible for labeling, annotating, and curating data sets to help improve machine learning models. Your daily tasks often include reviewing text, images, or audio and providing accurate labels according to detailed guidelines. You will frequently collaborate with data scientists, engineers, and other trainers to ensure consistency and quality in the data. This collaborative environment offers valuable exposure to the AI development process, and high performers often have opportunities to advance into more specialized roles over time.

What is the difference between Entry Level Ai Data Trainer vs Data Annotator?

AspectEntry Level Ai Data TrainerData Annotator
Required CredentialsHigh school diploma or equivalent; some roles prefer basic technical skillsHigh school diploma or equivalent; no specialized certifications typically needed
Work EnvironmentOffice or remote; collaborative with AI teamsOffice or remote; focused on labeling data
Employer & Industry UsageTech companies, AI startups, research labsTech companies, data labeling services, AI firms

While both roles involve working with data, Entry Level Ai Data Trainers focus on training AI models by providing structured data and feedback, often requiring some technical understanding. Data Annotators primarily label and categorize data to prepare datasets for AI training. The roles are similar in work environment and industry but differ in responsibilities and skill requirements.

What are the most commonly searched types of Ai Data Trainer jobs in California?

The most popular types of Ai Data Trainer jobs in California are:

What are popular job titles related to Entry Level Ai Data Trainer jobs in California?

For Entry Level Ai Data Trainer jobs in California, the most frequently searched job titles are:

What job categories do people searching Entry Level Ai Data Trainer jobs in California look for?

The top searched job categories for Entry Level Ai Data Trainer jobs in California are:

What cities in California are hiring for Entry Level Ai Data Trainer jobs?

Cities in California with the most Entry Level Ai Data Trainer job openings:

Infographic showing various Entry Level Ai Data Trainer job openings in California as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 13% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Synthetic Data Engineer (AI Data/Training)

Hyphen Connect Limited

San Francisco, CA • On-site

$134K - $162K/yr

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

We are seeking a talented and innovative Synthetic Data Engineer. In this role, you will design and implement domain-specific synthetic data generation pipelines, ensuring high-quality data management for training loops. Your expertise will drive the success of data processing and model training within the organization.

Responsibilities:

  • Design domain-specific synthetic data generation (SDG) pipelines via self-instruct and constitutional prompting.
  • Implement automated quality scoring and de-duplication systems.
  • Manage data pipelines that feed directly into SFT and DPO training loops.

Qualifications:

  • Proven experience building large-scale data pipelines (Airflow, Spark, Ray).
  • Deep knowledge of prompt engineering for data generation.
  • Familiarity with dataset distillation and bias mitigation.