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Seasonal Ai Data Annotation Jobs (NOW HIRING)

Sunday

Data Annotation Lead

Redwood City, CA · On-site

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.

Sunday Inc

Data Annotation Lead

Redwood City, CA · On-site

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 ...

GE HealthCare

Data Manager - AI Development

$94K - $141K/yr

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

Gehc

Data Manager - AI Development

Waukesha, WI · On-site

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

Dyna Robotics

Data Annotation Specialist

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.

Sunday

Technical Program Manager, Data Engine

Redwood City, CA · On-site

$157K - $204K/yr

... AI labs/data vendors • Technical skills to build tools for data annotation or collection • Ability to leverage AI to help improve productivity Company : Sunday is a robotics startup that builds ...

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All JobsSeasonal Ai Data Annotation Jobs

Seasonal Ai Data Annotation information

Is it hard to get hired for data annotation?

Getting hired for a seasonal AI data annotation role generally requires basic computer skills, attention to detail, and the ability to follow instructions. Many positions are entry-level and may not require prior experience, but strong accuracy and consistency are important. Competition can vary depending on the company and the volume of available work, but flexible schedules and remote work options often make these roles accessible to a wide range of applicants.

What is the difference between Seasonal Ai Data Annotation vs Data Labeler?

AspectSeasonal Ai Data AnnotationData Labeler
CredentialsHigh school diploma or equivalent; basic computer skillsHigh school diploma or equivalent; attention to detail
Work EnvironmentRemote or on-site; project-basedRemote or on-site; task-specific
Industry UsageAI and machine learning companies, tech firmsTech companies, data services, AI firms
Job FocusAnnotating data for AI training, often seasonal spikesLabeling data for machine learning models, often ongoing

Seasonal Ai Data Annotation involves annotating data during specific periods to support AI training, often with project-based work. Data Labelers perform similar tasks but may have more continuous or ongoing roles. Both roles require attention to detail and basic technical skills, but Seasonal Ai Data Annotation is typically tied to seasonal project demands in the AI industry.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior data scientists, machine learning engineers, or AI research directors, often involving advanced skills, extensive experience, and leadership responsibilities. These positions may include stock options, bonuses, or profit-sharing, contributing to the high total compensation. Such roles are usually found in large tech companies or organizations heavily investing in AI development.

How to become an AI data annotator?

To become an AI data annotator, you typically need strong attention to detail, good reading comprehension, and basic computer skills. Many positions require no formal degree and offer flexible schedules, often involving training on specific annotation tools or platforms. Building experience with data labeling and understanding AI workflows can improve job prospects.

How much do AI data annotators make?

AI data annotators typically earn between $10 and $20 per hour, depending on experience, location, and the complexity of the annotation tasks. Many positions are seasonal or part-time, often requiring attention to detail and familiarity with annotation tools or platforms.
More about Seasonal Ai Data Annotation jobs
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What are the most commonly searched types of Ai Data Annotation jobs? The most popular types of Ai Data Annotation jobs are:
What states have the most Seasonal Ai Data Annotation jobs? States with the most job openings for Seasonal Ai Data Annotation jobs include:
What job categories do people searching Seasonal Ai Data Annotation jobs look for? The top searched job categories for Seasonal Ai Data Annotation jobs are:
Seasonal Ai Data Annotation jobs near you
Infographic showing various Seasonal Ai Data Annotation job openings in the United States as of June 2026, with employment types broken down into 89% Full Time, 8% Part Time, and 3% Contract. Highlights an 99% Physical, and 1% Remote job distribution.

AI Data Annotation Specialist

BC Forward

Charlotte, NC

$56.08/hr

Other

Posted 18 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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