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Entry Level Data Annotation Tech Jobs (NOW HIRING)

BC Forward

AI Data Annotation Specialist

Charlotte, NC

$56.08/hr

... T consulting and workforce solutions firm providing services and support to Fortune 500 and ... We are seeking an AI Data Annotation Training Data Contractor to join our dynamic team. The ideal ...

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Data Annotator (Autonomous Vehicle / AI)

San Francisco, CA · On-site

$32 - $39/hr

The ideal candidate is detail-oriented, technically proficient in 2D and 3D annotation, and ... driving technologies. The quality and accuracy of annotated data are foundational to the ...

Isalys Group

Entry-Level Expert in Data Entry

San Antonio, TX · Remote

$15.50 - $20.75/hr

A willingness to learn and adapt to new technologies and systems. What We Offer : * Say goodbye to ... As a Remote Entry-Level Data Entry Specialist, you will not only improve your data handling ...

Arthur Lawrence

Data Annotator

Fremont, CA

Experience in autonomous vehicle data annotation, including LiDAR/Point Cloud and 2D image labeling ... Arthur Lawrence is a management and technology consulting firm providing enterprise-wide business ...

Amazon

Catalog Specialist, RCX

Bellevue, WA · On-site

Key job responsibilities • Work closely with our product, technology, and science teams to support Machine Learning (ML) models • Perform data annotation required to train and evaluate ML models ...

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Entry Level Data Annotation Tech information

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How much do entry level data annotation tech jobs pay per hour?

As of Jun 19, 2026, the average hourly pay for entry level data annotation tech in the United States is $19.34, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $21.39 per hour, depending on experience, location, and employer.

What is the difference between Entry Level Data Annotation Tech vs Entry Level Data Labeler?

AspectEntry Level Data Annotation TechEntry Level Data Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech-focusedRemote or on-site, tech-focused
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, autonomous vehicles

Both roles involve labeling data for AI training, requiring similar skills and environments. The main difference lies in terminology; 'Data Annotation Tech' emphasizes the technical aspect of annotation, while 'Data Labeler' is a more general term. Both are entry-level positions vital for AI development in tech industries.

What are some common challenges faced by Entry Level Data Annotation Techs, and how can they be managed?

Entry Level Data Annotation Techs often encounter challenges like maintaining focus during repetitive tasks, ensuring accuracy under tight deadlines, and adapting to evolving annotation guidelines. To manage these, it's helpful to take regular breaks, double-check your work, and actively seek feedback from supervisors. Collaborating with teammates and participating in training sessions can also improve both speed and consistency, making the work more manageable and rewarding.

Can I use ChatGPT for data annotation?

Entry Level Data Annotation Technicians can use ChatGPT to assist with labeling and categorizing data, especially for text-based tasks. However, human oversight is essential to ensure accuracy and consistency, as AI tools may not fully understand context or nuances in complex data annotation projects.

What is an Entry Level Data Annotation Tech?

An Entry Level Data Annotation Tech is responsible for labeling and categorizing data, such as images, text, or audio, to help train machine learning models. This role typically involves using specialized software to accurately tag and classify data according to specific guidelines. It is a foundational position within the field of artificial intelligence and data science, requiring attention to detail and consistency. No advanced technical skills are usually required, making it a suitable entry point for those interested in AI or data-related careers.

Is it easy to get hired for data annotation?

Entry level data annotation jobs are generally accessible to beginners, as they often require minimal prior experience and focus on basic labeling skills. Employers typically look for attention to detail and the ability to follow instructions, and training is usually provided. Competition can vary depending on the platform and demand, but overall, these roles tend to have relatively straightforward hiring processes.

Can I do data annotation with no experience?

Entry level data annotation jobs typically do not require prior experience, as training is often provided to teach specific tools and guidelines. Basic computer skills and attention to detail are usually sufficient to start, making it accessible for beginners. Developing familiarity with annotation tools and understanding data labeling standards can improve job performance and opportunities for advancement.

How to get into data annotation tech?

To get into data annotation tech, candidates typically need basic computer skills and attention to detail. Many entry-level roles require no formal degree, but familiarity with tools like labeling platforms and understanding data types can be helpful. Gaining experience through online tutorials or certifications in data labeling can improve job prospects.

What are the key skills and qualifications needed to thrive as an Entry Level Data Annotation Tech, and why are they important?

To thrive as an Entry Level Data Annotation Tech, you need strong attention to detail, basic computer literacy, and a high school diploma or equivalent. Familiarity with annotation software, data labeling platforms, and basic spreadsheet tools is typically required. Patience, consistency, and effective communication help ensure accuracy and efficient teamwork. These skills and qualities are essential for delivering high-quality labeled data that supports machine learning and AI development.
More about Entry Level Data Annotation Tech jobs
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Entry Level Data Annotation Tech jobs near you
Infographic showing various Entry Level Data Annotation Tech job openings in the United States as of June 2026, with employment types broken down into 80% Full Time, 12% Part Time, and 8% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $40,220 per year, or $19.3 per hour.

AI Data Annotation Specialist

BC Forward

Charlotte, NC

$56.08/hr

Other

Posted 24 days ago

Job description

Job Title: Application Programmer III Location: Charlotte, NC Duration: Contract - 12 months Pay Range: $56.08/hr (W2) Job ID: 373918 About BCforward BCforward is a leading global IT consulting and workforce solutions firm providing services and support to Fortune 500 and government clients. Founded in 1998, BCforward has grown with our customers needs into a full-service business solutions provider. With delivery centers and offices across North America and India, we take pride in building long-term relationships and delivering excellence through innovation, collaboration, and integrity.

Job Description We are seeking an AI Data Annotation Training Data Contractor to join our dynamic team. The ideal candidate will have strong experience in AI/ML data labeling, QA, and evaluation across NLP, information retrieval, entity extraction, routing/classification, semantic search, and RAG/LLM applications, and a proven ability to deliver accurate, consistent annotations and evaluation datasets at scale. Responsibilities: Annotate and label large datasets for AI/ML training and evaluation tasks across text, tabular, and retrieval workflows.

Create labels for query classification, intent detection, entity and time extraction, metric identification, semantic similarity, relevance ranking, and document retrieval quality. Tag and classify user queries, documents, entities, metadata, tool routing, structured vs. unstructured query type, human preference, and LLM response quality.

Perform QA reviews to ensure consistency, accuracy, completeness, and adherence to acceptance criteria; escalate ambiguities and edge cases. Participate in inter-annotator agreement, calibration sessions, and feedback loops to refine dataset quality. Assist in building evaluation datasets, benchmark suites, and golden sets for classifiers, retrieval systems, and LLM generation quality.

Review AI outputs, provide structured scoring and feedback, and help identify failure modes, hallucinations, routing issues, and retrieval gaps. Follow detailed annotation specifications and operational procedures; document decisions, edge cases, and standards. Support taxonomy and schema refinement; organize datasets, metadata, and labeling workflows across tools and platforms.

Work effectively within Agile development practices and collaborate with data science, ML engineering, and platform teams. Required Skills & Qualifications: Bachelor's degree or equivalent practical experience. Experience with data annotation, data labeling, QA, research operations, or analytical workflows.

Ability to follow complex technical instructions and detailed labeling guidelines with high accuracy. Strong attention to detail, organizational skills, and written communication. Comfort with large datasets, structured processes, spreadsheets, and labeling interfaces.

Ability to work independently, manage priorities, and meet deadlines in a fast-paced environment. Preferred Skills: Familiarity with RAG, LLM evaluation, semantic search, and information retrieval concepts. Experience working in Agile/Scrum settings and collaborating with ML engineering teams.

Why BCforward? At BCforward, we believe in advancing lives and careers. When you join our team, you gain access to: Competitive compensation and benefits.

Opportunities for growth with global clients. A supportive, inclusive culture that values innovation and people. Exposure to cutting-edge technologies and projects.

About Our Commitment BCforward is an equal opportunity employer. We value diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, or veteran status.

Interested? Apply Now! If this sounds like the right opportunity for you, please apply with your most recent resume.

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