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Intern Ai Data Annotation Jobs (NOW HIRING)

Responsibilities : • Build a data annotation team • Manage the people side of data annotations ... Sunday is a robotics startup that builds home robots that utilize AI to assist with household tasks.

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 ...

Track annotation progress, throughput, and quality metrics. * Maintain annotation dashboards to ensure timely delivery aligned with AI development milestones. 4. Data Governance & Compliance Support

As a Data Annotation Specialist, you will be pivotal in iterating on our AI system by annotating data on various tasks performed by robots, directly influencing the performance of robotic arms.

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How much do intern ai data annotation jobs pay per hour?

As of Jun 12, 2026, the average hourly pay for intern ai data annotation in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Intern AI Data Annotation Specialist, and why are they important?

To thrive as an Intern AI Data Annotation Specialist, you need strong attention to detail, basic data handling skills, and familiarity with common data formats, often supported by a background in computer science or related fields. Experience with data labeling tools, annotation platforms, and sometimes basic knowledge of Python or similar scripting languages is typically required. Reliability, patience, and effective communication are essential soft skills for ensuring accuracy and collaborating with team members. These competencies are crucial for generating high-quality annotated datasets that enable accurate machine learning model development.

What does a typical day look like for an AI Data Annotation Intern, and how do they collaborate with other teams?

As an AI Data Annotation Intern, your typical day involves labeling and categorizing data such as images, audio, or text to train machine learning models. You’ll use specialized annotation tools and follow detailed guidelines to ensure consistency and accuracy. Collaboration is key—you’ll often communicate with data scientists, machine learning engineers, and project managers to clarify requirements and provide feedback on ambiguous cases. This teamwork helps ensure the data you annotate aligns with project goals and quality standards, making your contributions vital to the development of AI solutions.

What does an Intern AI Data Annotation do?

An Intern AI Data Annotation is responsible for labeling and categorizing data, such as images, text, or audio, to help train artificial intelligence models. They ensure data is accurately tagged according to specific guidelines so that AI systems can learn to recognize patterns or make predictions. This role often involves using specialized annotation tools and requires attention to detail to maintain high-quality datasets. Interns may also assist with reviewing and correcting data, as well as collaborating with data scientists and engineers to improve annotation processes.
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AI Data Annotation Specialist

BC Forward

Charlotte, NC

$56.08/hr

Other

Posted 17 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.