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Ai Data Annotation Jobs (NOW HIRING)

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 ...

This role is about building and leading a world class in-house data annotation team that is able to ... Ability to leverage AI to help improve productivity At Sunday Robotics, we're building technology ...

Responsibilities : • Build and improve quality assurance and compliance systems across AI data annotation projects • Design quality standards, review processes, escalation workflows, and ...

Collaborate with data science and platform teams to deploy scalable AI solutions. Annotate and label datasets to support training, evaluation, and alignment workflows across NLP and retrieval tasks.

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Ai Data Annotation information

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

To excel in AI Data Annotation, you need strong attention to detail, data accuracy, and a basic understanding of data labeling concepts, typically supported by a high school diploma or equivalent. Familiarity with annotation tools such as Labelbox, Supervisely, or similar platforms is often required, and some employers may value basic programming or machine learning course certifications. Excellent communication, the ability to follow detailed guidelines, and time management are valuable soft skills in this role. These skills ensure the production of high-quality annotated datasets, which are critical for training reliable AI and machine learning models.

What are the typical daily tasks and team dynamics for an AI Data Annotation position?

As an AI Data Annotator, your typical day involves labeling and tagging data such as images, audio, or text according to specific project guidelines, often using specialized annotation software. You may work independently or as part of a remote or on-site team, collaborating with data scientists and quality assurance specialists to ensure consistency and accuracy. Regular feedback sessions and quality checks are common to maintain high annotation standards. The role can be repetitive, but attention to detail and clear communication with team members help create datasets that are crucial for training effective AI systems.

What is an AI Data Annotation job?

An AI Data Annotation job involves labeling or tagging data, such as text, images, audio, or video, to train machine learning models. Annotators ensure that data is accurately categorized so AI systems can learn to recognize patterns and make predictions. This work is crucial for improving AI applications like self-driving cars, chatbots, and image recognition software. It often requires attention to detail and familiarity with specific annotation tools.

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Infographic showing various Ai Data Annotation job openings in the United States as of June 2026, with employment types broken down into 2% As Needed, 96% Full Time, 1% Part Time, and 1% Nights. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution.

AI Data Annotation Specialist

BC Forward

Charlotte, NC • On-site

$56.08/hr

Other

Posted yesterday


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.