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Entry Level Ai Data Trainer Jobs (NOW HIRING)

Flexjet LLC

AI Data Engineer

Cleveland, OH · On-site

$90 - $130/hr

Flexjet is seeking a detail-oriented AI Data Engineer to build and maintain data infrastructure ... Develop and manage datasets for model training, validation, and inference * Collaborate with ML ...

eTeam

AI & Data - Data Engineer

Seattle, WA · On-site

$130K - $156K/yr

... training and inference. • Implement data quality tests, documentation, and lineage in DBT • ... AI/Data Science) team to provide feature ready datasets. Qualifications : Required : • Hands-on ...

Elmington

AI Data Analyst

Nashville, TN · On-site

This role partners with the Director of Data Analytics to develop and implement AI-based tools and ... training, and experience. In compliance with local, state, and federal laws, we provide equal ...

C the Signs

AI Data Engineer

New York, NY · On-site +1

$125K - $150K/yr

... training and refinement Key Responsibilities * Collaborate with data scientists and machine ... Joining C the Signs is not just about building AI; it's about shaping the future of healthcare. If ...

C the Signs

AI Data Engineer

Boston, MA · Remote

$117K - $140K/yr

... training and refinement Key Responsibilities * Collaborate with data scientists and machine ... Joining C the Signs is not just about building AI; it's about shaping the future of healthcare. If ...

C the Signs

AI Data Engineer

New York, NY · Remote

$117K - $140K/yr

... training and refinement Key Responsibilities * Collaborate with data scientists and machine ... Joining C the Signs is not just about building AI; it's about shaping the future of healthcare. If ...

C the Signs

AI Data Engineer

Boston, MA · On-site +1

$124K - $149K/yr

... training and refinement Key Responsibilities * Collaborate with data scientists and machine ... Joining C the Signs is not just about building AI; it's about shaping the future of healthcare. If ...

C the Signs

AI Data Engineer

Boston, MA · On-site +1

$124K - $149K/yr

... training and refinement Key Responsibilities * Collaborate with data scientists and machine ... Joining C the Signs is not just about building AI; it's about shaping the future of healthcare. If ...

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Entry Level Ai Data Trainer information

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How much do entry level ai data trainer jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for entry level ai data trainer in the United States is $31.24, according to ZipRecruiter salary data. Most workers in this role earn between $19.95 and $35.58 per hour, depending on experience, location, and employer.

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.

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Entry Level Ai Data Trainer jobs near you
Infographic showing various Entry Level Ai Data Trainer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $64,984 per year, or $31.2 per hour.

AI Data Engineer

Flexjet LLC

Cleveland, OH • On-site

$90 - $130/hr

Other

Posted 29 days ago

Flexjet rating

8.2

Company rating: 8.2 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

19th of 67 rated aviation services

Job description

Current job opportunities are posted here as they become available.

Flexjet is seeking a detail-oriented AI Data Engineer to build and maintain data infrastructure that powers machine learning and AI systems. In this role, you will work closely with data scientists, ML engineers, and software teams to ensure high-quality, reliable, and scalable data pipelines for AI applications.

DUTIES & RESPONSIBILITIES
  • Design, build, and maintain data pipelines for AI and machine learning workflows
  • Collect, clean, and preprocess structured and unstructured data
  • Develop and manage datasets for model training, validation, and inference
  • Collaborate with ML engineers and data scientists to support model development
  • Ensure data quality, integrity, and availability across systems
  • Optimize data storage and retrieval for performance and scalability
  • Implement data governance, security, and compliance best practices
  • Monitor and troubleshoot data pipeline issues
REQUIRED SKILLS & QUALIFICATIONS
  • Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field (or equivalent experience)
  • Strong programming skills in Python and/or SQL
  • Understanding of data engineering concepts (ETL/ELT, data modeling, data warehousing)
  • Familiarity with machine learning workflows and data requirements
  • Experience with data processing tools (e.g., Pandas, Spark)
  • Knowledge of relational and non-relational databases
  • Basic understanding of cloud platforms (AWS, Azure, or Google Cloud)
PREFERRED QUALIFICATIONS
  • Experience supporting machine learning or AI projects
  • Familiarity with big data technologies (e.g., Apache Spark, Kafka, Hadoop)
  • Experience with data pipeline orchestration tools (e.g., Airflow, Prefect)
  • Knowledge of MLOps practices and tools
  • Experience working with unstructured data (text, images, etc.)
  • Understanding of data governance and privacy standards
  • Strong analytical and problem-solving skills
  • Attention to detail and data quality
  • Ability to work with cross-functional teams
  • Ability to manage multiple data workflows
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