1

Temporary Ai Data Collection Jobs (NOW HIRING)

Track data collection and annotation budget. 3. Annotation & Labeling Oversight * Coordinate data ... Support execution of AI data management practices including: * Data control planning * Data ...

Track data collection and annotation budget. 3. Annotation & Labeling Oversight * Coordinate data ... Support execution of AI data management practices including: * Data control planning * Data ...

Data Collection

San Jose, CA · On-site

$150K - $250K/yr

While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on ... About the Role You'll own data collection at Hark - the programs, the vendors, and the pipelines ...

While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on ... About the Role You'll own data collection at Hark - the programs, the vendors, and the pipelines ...

Power the Future of AI 🤖 Get hands-on with cutting-edge robotics and help train the next ... If eligible, the benefits available for this temporary role may include the following: • Medical ...

$14.30/hr

(Netherlands BASED) AI Data Collector - Turn the World Into Your Workplace! Do you love scavenger ... Never complete data collection in a way that would risk injury to you or others. Important: This ...

next page

Showing results 1-20

Temporary Ai Data Collection information

See salary details

$16

$25

$31

How much do temporary ai data collection jobs pay per hour?

As of Jun 14, 2026, the average hourly pay for temporary ai data collection in the United States is $25.31, according to ZipRecruiter salary data. Most workers in this role earn between $23.32 and $25.96 per hour, depending on experience, location, and employer.

What is temporary AI data collection?

Temporary AI data collection is a short-term job where individuals gather, label, or organize data used to train artificial intelligence systems. This can involve tasks such as taking photos, recording audio, transcribing text, or annotating images and videos according to specific guidelines. The work is often project-based and helps improve the accuracy and performance of AI models. People in these roles play a vital part in ensuring that AI systems learn from diverse, well-organized, and correctly labeled data.

What are the key skills and qualifications needed to thrive as a Temporary AI Data Collection Specialist, and why are they important?

To thrive as a Temporary AI Data Collection Specialist, you need attention to detail, basic data entry skills, and the ability to follow structured guidelines, often with a high school diploma or equivalent. Familiarity with data annotation platforms, spreadsheets, and cloud-based collaboration tools is typically required. Reliability, adaptability, and strong communication skills help ensure accurate data collection and effective teamwork. These skills are important for producing high-quality datasets that improve AI models and support project goals.

What is an AI data collection job?

An AI data collection job involves gathering and labeling data, such as images, text, or audio, to train machine learning models. Workers typically review, categorize, or annotate data using specialized tools and may work remotely on flexible schedules.

What is a $900,000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, often involving advanced skills in machine learning, data analysis, and programming. Such roles may include AI research scientists, machine learning engineers, or senior data scientists working in tech companies or research institutions, and they usually require specialized expertise and experience.

What is the easiest AI job to get?

For a temporary AI data collection role, entry-level positions are generally the easiest to obtain, often requiring minimal prior experience and focusing on tasks like labeling or annotating data. These jobs typically involve working with simple tools and can be suitable for individuals with basic computer skills and attention to detail.

What is the difference between Temporary Ai Data Collection vs Data Annotator?

AspectTemporary Ai Data CollectionData Annotator
CredentialsBasic computer skills, sometimes familiarity with data collection toolsAttention to detail, basic technical skills, sometimes training in annotation tools
Work EnvironmentRemote or on-site, often flexible hoursRemote or on-site, focused on labeling data
Industry UsageUsed in AI training data gathering, machine learning projectsUsed in preparing datasets for AI models, image/video/text annotation

Temporary Ai Data Collection involves gathering raw data for AI training, often requiring data sourcing skills. Data Annotator focuses on labeling and annotating data to make it usable for machine learning. Both roles are essential in AI development but differ in their specific tasks and skill requirements.

Which 3 jobs will survive AI?

For a Temporary AI Data Collection role, jobs that involve creative thinking, complex problem-solving, and emotional intelligence are more likely to survive AI automation. These include roles such as data analysts, AI trainers, and customer service representatives, which require human judgment, nuanced understanding, and interpersonal skills. Skills in critical thinking, communication, and adaptability will remain valuable in these fields.

What does a typical day look like for someone in a Temporary AI Data Collection role?

In a Temporary AI Data Collection position, your daily tasks often involve gathering, labeling, and organizing large sets of data—such as images, text, or audio—that will be used to train machine learning models. You may work independently or as part of a team, following specific guidelines to ensure data accuracy and consistency. Attention to detail is crucial, as even small errors can impact the quality of AI systems. Collaboration with project managers or data scientists is common, especially when clarifying data requirements or resolving ambiguities. The work environment is typically fast-paced, with clear deadlines and performance metrics to meet.
More about Temporary Ai Data Collection jobs
What cities are hiring for Temporary Ai Data Collection jobs? Cities with the most Temporary Ai Data Collection job openings:
What are the most commonly searched types of Ai Data Collection jobs? The most popular types of Ai Data Collection jobs are:
What states have the most Temporary Ai Data Collection jobs? States with the most job openings for Temporary Ai Data Collection jobs include:
Infographic showing various Temporary Ai Data Collection job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 86% Full Time, 12% Part Time, and 1% Temporary. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $52,640 per year, or $25.3 per hour.
Head of AI Data Collection & Operations , Frontier AI & Robotics

Head of AI Data Collection & Operations , Frontier AI & Robotics

Amazon

San Francisco, CA

Full-time

Posted 18 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,847 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers


Job description

Join Amazon's Frontier AI & Robotics team and lead the laboratory operations that enable breakthrough research in embodied intelligence. As Head of Lab Operations, you'll lead the on-the-ground teams that power our AI research programs-directing a large contractor workforce, managing our robot fleet, overseeing data collection campaigns, and ensuring our test environments give researchers and engineers the high-quality operational foundation they need to move fast. Your leadership directly shapes the velocity and quality of our AI research by keeping robots healthy, data pipelines flowing, and test environments ready to support the next wave of innovation.
Key job responsibilities
Lead, develop, and retain a 40-50 person contractor workforce spanning robot fleet operations, AI data collection, and test environment construction; establish clear performance expectations, career development pathways, and a culture of ownership, safety, and continuous improvement
Own robot fleet management end-to-end-maintain robot health and readiness, drive preventive and corrective maintenance programs, track fleet utilization and uptime KPIs, and ensure robots are mission-ready to support research and data collection operations at all times
Direct data collection operations that feed AI research pipelines; coordinate with AI researchers and data engineering teams to plan, execute, and quality-assure data collection campaigns, ensuring operational fidelity and data integrity at scale
Develop, build out, and sustain test environments and experimental infrastructure that enable researchers and engineers to evaluate robotic systems efficiently; manage test cell configuration, instrumentation readiness, and environment lifecycle from initial buildout through ongoing operations
Define, track, and report operational KPIs-including robot fleet uptime, data collection throughput, test environment availability, safety performance, and cost efficiency-using metrics to drive decisions and communicate operational health to senior leadership
Scale operational processes, standard operating procedures (SOPs), and workforce capabilities as research programs grow; build infrastructure and playbooks that maintain quality and speed as scope expands
A day in the life
As the Head of AI Data Collection & Operations at FAR, you set strategic direction for the operational capabilities that drive research velocity: shaping how the organization manages its robot fleet, structures its data collection programs, and builds the infrastructure that gives researchers the freedom to innovate without friction

You are a key voice in senior leadership forums, translating operational performance into strategic insights, championing investments that build long-term organizational capability, and ensuring that lab operations function as a genuine competitive advantage. You invest in your team's growth, forge deep partnerships with research and engineering leadership, and make the resource allocation decisions that keep FAR's operational foundation ahead of an ambitious and fast-moving research roadmap. You define, develop, and drive improvement on key lab performance indicators to ensure we are operating at maximum velocity and efficiency.
About the team
At Frontier AI & Robotics, we're not just advancing robotics - we're reimagining it from the ground up

Our team is building the future of intelligent robotics through frontier foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios.
What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models

Our work spans the full spectrum of robotics intelligence - from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations.


What Amazon employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Amazon logo

About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US