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Hourly Ai Data Annotation Jobs (NOW HIRING)

Besimple AI

Strategic Projects Lead -- Audio Data

$53 - $71.75/hr

Required : • 3-7+ years of experience in data operations, AI data delivery, annotation operations, localization project management, marketplace operations, program management, or similar roles. • ...

Q ANALYSTS LLC

Data Annotation Technician

Kirkland, WA · On-site +1

... AI) and machine learning (ML). Q Analysts is headquartered in San Jose, CA with a presence ... Q Analysts is looking for Data Annotation Technicians to support Ground Truth Data Collection ...

Encord

Human Data Operations Strategist

San Francisco, CA · On-site

$150K - $230K/yr

Oversee data annotation projects, translating complex AI and machine learning requirements into clear workflows and instructions for data annotation teams * Ensure the highest standards of data ...

Encord

Human Data Operations Strategist

San Francisco, CA · On-site

$150K - $230K/yr

Oversee data annotation projects, translating complex AI and machine learning requirements into clear workflows and instructions for data annotation teams * Ensure the highest standards of data ...

RWS Group

$120K - $140K/yr

RWS Train AI helps our clients address this challenge head-on. With a seamless blend of ... Oversee complex workstreams including annotation, labeling, linguistic validation, data operations ...

RWS Group

$120K - $140K/yr

RWS Train AI helps our clients address this challenge head-on. With a seamless blend of ... Oversee complex workstreams including annotation, labeling, linguistic validation, data operations ...

RWS Group

Program Manager - Train AI Data Services

$120K - $140K/yr

RWS Train AI helps our clients address this challenge head-on. With a seamless blend of ... Oversee complex workstreams including annotation, labeling, linguistic validation, data operations ...

Mercor

Network Engineer - Data Annotation

New York, NY · Remote

$50 - $70/hr

About the job Mercor connects elite creative and technical talent with leading AI research labs ... Position: Network Engineer - Data for Autonomous Systems annotation Type: Contract Compensation ...

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Hourly Ai Data Annotation information

How much is $70,000 a year hourly?

For an Hourly AI Data Annotation role, earning $70,000 annually typically translates to about $33.65 per hour based on a standard 40-hour workweek and 52 weeks per year. This calculation does not account for taxes, benefits, or overtime, which can affect the actual hourly rate. The exact hourly wage may vary depending on the company's pay structure and work schedule.

What is an Hourly AI Data Annotation job?

An Hourly AI Data Annotation job involves labeling, tagging, or categorizing data—such as images, text, or audio—to help train machine learning models. Annotators follow specific guidelines to ensure that the data is accurately labeled so that AI systems can learn to recognize patterns and make decisions. These jobs are typically paid by the hour and may require attention to detail, consistency, and sometimes familiarity with specialized annotation tools. This work is essential for improving the accuracy and usefulness of artificial intelligence applications.

What are some common challenges faced by hourly AI data annotators, and how can they be managed?

Hourly AI data annotators often encounter challenges such as repetitive tasks, maintaining high accuracy under time constraints, and adapting to evolving project guidelines. To manage these, it's important to take regular breaks to avoid fatigue, stay up to date with training materials, and communicate proactively with team leads if instructions are unclear. Many teams use collaborative tools and regular feedback sessions to support annotators and ensure consistent quality, making teamwork and attention to detail vital for success in this role.

Is 2026 going to be hot?

As an Hourly AI Data Annotation worker, weather conditions like temperature are unrelated to the job. Weather forecasts for 2026 are not available, but climate trends suggest that some regions may experience warmer temperatures due to climate change. The job typically involves working indoors with data labeling tools and does not depend on weather conditions.

What does hourly mean?

In an hourly AI data annotation job, hourly refers to the pay rate calculated based on the number of hours worked. Workers are typically paid a set amount for each hour they spend annotating data, and the total earnings depend on the total hours completed, often tracked with time management tools or software.

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

To thrive as an AI Data Annotator, you need strong attention to detail, 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 or Supervisely, and basic computer proficiency, are often required. Critical thinking, consistency, and effective communication are valuable soft skills in this role. These skills ensure high-quality, reliable data that directly improves the performance of AI and machine learning models.

What is 20 an hour hourly?

For an Hourly AI Data Annotation role, earning $20 an hour means you are paid $20 for each hour of work completed. This rate is common for entry-level or part-time data annotation tasks, which often require attention to detail and familiarity with annotation tools. The total earnings depend on the number of hours worked per week or month.

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

AspectHourly Ai Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or in-office, flexible hoursRemote or in-office, flexible hours
Industry UsageAI, machine learning, tech companiesAI, machine learning, tech companies
Job FocusAnnotating data for AI training, often with specific instructionsLabeling data to help AI models learn, often similar tasks

Hourly Ai Data Annotation and Data Labeler roles are similar, focusing on preparing data for AI systems. The main difference lies in terminology; 'Hourly Ai Data Annotation' emphasizes the paid hourly aspect and the specific task of annotating data for AI training, while 'Data Labeler' is a broader term used interchangeably in the industry. Both roles require similar skills and are used in the same industry sectors.

More about Hourly Ai Data Annotation jobs
What cities are hiring for Hourly Ai Data Annotation jobs? Cities with the most Hourly Ai Data Annotation job openings:
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 Hourly Ai Data Annotation jobs? States with the most job openings for Hourly Ai Data Annotation jobs include:
What job categories do people searching Hourly Ai Data Annotation jobs look for? The top searched job categories for Hourly Ai Data Annotation jobs are:
Hourly Ai Data Annotation jobs near you
Infographic showing various Hourly Ai Data Annotation job openings in the United States as of June 2026, with employment types broken down into 14% As Needed, 14% Full Time, 14% Part Time, 44% Contract, and 14% Nights. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution.

Strategic Projects Lead -- Audio Data

Besimple AI

Remote

$53 - $71.75/hr

Full-time

Posted 4 days ago

Job description

Job Summary:
Besimple AI is building the data and benchmark infrastructure for the next generation of voice AI. They are seeking a Strategic Projects Lead — Audio Data to manage high-priority audio data projects, ensuring they meet customer expectations from initiation to delivery.
Responsibilities:
• Own audio data collection and annotation projects from kickoff through final customer delivery.
• Translate customer requirements into project specs, contributor workflows, annotation guidelines, QA rubrics, acceptance criteria, and delivery plans.
• Configure and operate projects through Besimple’s internal platform.
• Design and run pilots to validate task design, contributor fit, audio quality, tooling, throughput, cost, and QA process before scaling.
• Manage day-to-day execution across contributors, annotators, reviewers, QA leads, and internal tools.
• Monitor project health across volume, quality, rejection rate, rework rate, cost, margin, and timeline risk.
• Identify platform gaps that prevent projects from scaling, then write clear product requirements or feature requests.
• Partner with engineering/product to build or improve tools for project setup, contributor workflows, QA, review, payments, reporting, and delivery.
• Partner with contributor growth to ensure we have the right supply by language, accent, demographic, device, skill set, or task type.
• Build dashboards, trackers, and operating cadences for project execution.
• Communicate project status, risks, tradeoffs, and blockers clearly to founders, internal teams, and customers.
• Create repeatable playbooks for future audio collection, transcription, annotation, and QA projects.
• Drive root-cause analysis when projects miss quality, cost, or timeline expectations.
Qualifications:
Required:
• 3–7+ years of experience in data operations, AI data delivery, annotation operations, localization project management, marketplace operations, program management, or similar roles.
• Proven experience owning projects end to end, from ambiguous requirements to final delivery.
• Strong operator mindset: you can break down vague goals, create a plan, execute quickly, and unblock yourself.
• Experience managing complex workflows involving distributed contributors, reviewers, contractors, vendors, or large-scale data operations.
• Strong product sense; able to identify when tooling or platform features are needed and translate operational pain points into clear product requirements.
• Strong analytical ability; comfortable with spreadsheets, dashboards, funnel metrics, QA metrics, and operational KPIs.
• Excellent written communication; able to write clear instructions, guidelines, SOPs, customer updates, and internal product specs.
• Strong quality judgment and attention to detail.
• Comfortable balancing quality, speed, cost, customer requirements, contributor experience, and platform constraints.
• Comfortable working in ambiguity and building processes from scratch.
• High ownership, low ego, and willingness to get hands-on with messy operational details.
Preferred:
• Experience at a data labeling, AI data, localization, or crowdsourcing company such as Scale AI, Surge AI, Appen, TELUS Digital, RWS, TransPerfect DataForce, Welocalize, Lilt, Turing, DataAnnotation, Outlier, Remotasks, or similar.
• Experience owning end-to-end delivery of data collection, annotation, transcription, evaluation, or QA projects.
• Experience with audio, speech, voice, ASR, TTS, speech-to-speech, transcription, podcast/audio production, or linguistic data.
• Experience building or improving internal tools, workflow systems, annotation platforms, QA systems, or contributor-facing products.
• Experience designing annotation guidelines, QA rubrics, reviewer training, or calibration workflows.
• Experience with multilingual or locale-specific data projects.
• Experience managing large distributed teams of contributors, reviewers, contractors, or vendors.
• Basic SQL, Python, Airtable, Retool, no-code automation, or workflow tooling experience.
Company:
besimple AI is a software company that provides AI-based data annotation infrastructure designed for model training. Founded in 2025, the company is headquartered in Redwood City, USA, with a team of 2-10 employees. The company is currently Early Stage.

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