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Temporary Ai Data Collection Jobs in California (NOW HIRING)

Data Strategy Associate

San Jose, CA · On-site

$100K - $180K/yr

Report deployment progress and metrics to the AI Data Collection Manager Requirements: * 3-5 years in program management (especially for operations), consulting, investment banking, startup project ...

Data Strategy Associate

San Jose, CA · On-site

$100K - $180K/yr

Report deployment progress and metrics to the AI Data Collection Manager Requirements: * 3-5 years in program management (especially for operations), consulting, investment banking, startup project ...

... data collection, expanding data acquisition opportunities in real-world scenarios, and ensuring the delivery of high-quality, multimodal data for embodied AI model training. If you are deeply ...

... data collection, expanding data acquisition opportunities in real-world scenarios, and ensuring the delivery of high-quality, multimodal data for embodied AI model training. If you are deeply ...

AI Data Operations Lead

Milpitas, CA · On-site

$145K - $205K/yr

You will be the technical owner and lead for the full embodied systems stack - the onboard AI system, the data collection system, the teleoperation systems, and the on-robot reinforcement learning ...

AI Data Operations Lead

Milpitas, CA · On-site

$145K - $205K/yr

You will be the technical owner and lead for the full embodied systems stack - the onboard AI system, the data collection system, the teleoperation systems, and the on-robot reinforcement learning ...

Data Collection Associate I Are you interested in working with the World's leading AI-powered Quality Engineering Company? Ready to advance your career, team up with global thought leaders across ...

Collect accurate, high-quality motion data to support the training of AI models. * Monitor ... If eligible, the benefits available for this temporary role may include the following: * Medical ...

Showing results 41-60

Temporary Ai Data Collection information

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 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.

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 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.

What are the most commonly searched types of Ai Data Collection jobs in California?

The most popular types of Ai Data Collection jobs in California are:

What are popular job titles related to Temporary Ai Data Collection jobs in California?

For Temporary Ai Data Collection jobs in California, the most frequently searched job titles are:

What job categories do people searching Temporary Ai Data Collection jobs in California look for?

The top searched job categories for Temporary Ai Data Collection jobs in California are:

What cities in California are hiring for Temporary Ai Data Collection jobs?

Cities in California with the most Temporary Ai Data Collection job openings:

Infographic showing various Temporary Ai Data Collection job openings in California as of August 2026, with employment types broken down into 70% Full Time, and 30% Part Time. Highlights an 74% In-person, and 26% Remote job distribution.

Data Partnership Manager

Maxinsights Corporation

Santa Clara, CA • On-site

$90 - $135/hr

Other

Re-posted 18 days ago


Job description

We are seeking a passionate and execution-driven Supply Chain BD leader to spearhead data collection scenario expansion and crowdsourced operations for embodied robotics. You will participate in building and operating a crowdsourcing supply chain model for embodied robot data collection, expanding data acquisition opportunities in real-world scenarios, and ensuring the delivery of high-quality, multimodal data for embodied AI model training. If you are deeply interested in building a "data production network" and are willing to accumulate experience through frontline, hands-on operations to achieve rapid growth, this is an excellent opportunity to join a team in the cutting‑edge field of AI infrastructure.

Core Responsibilities Scenario Expansion & Supply Chain Ecosystem Building

Assist in planning and executing the expansion of data collection scenarios for embodied robots, going deep into the frontline to uncover data collection opportunities in real‑world environments such as factories, households, retail, healthcare, and logistics.

Participate in building and operating the data collection "crowdsourcing model," assisting in the management of a diverse supply chain of data collectors (e.g., community residents, freelancers, part-time workers, etc.).

Assist in establishing systems for collector recruitment, training, task dispatching, incentives, and retention to ensure a continuous and stable data supply chain.

Crowdsourcing Platform & Data Pipeline Management

Take charge of the day‑to‑day operations of the entire data collection workflow, including task creation, collection execution, initial quality screening, and data delivery.

Collaborate with product and technical teams to provide feedback on the user experience of crowdsourced collection tools, driving iterative optimization of these tools.

Execute quality control processes to ensure the validity, accuracy, and compliance of the collected data.

Operational Empowerment & Scaled Growth

Assist in formulating scaling strategies to cover more regions and scenarios, increasing the density and production capacity of the data network.

Identify and resolve common issues in daily operations (such as capacity fluctuations, cost control, collection team activity rates, etc.) to continuously optimize operational efficiency.

Collaborate with the Business Development (BD) team to translate crowdsourced collection capabilities into delivery support for commercialized data products.

Team & Vendor Management

Responsible for building, training, and managing a small data operations team on a daily basis (including collection specialists, QA specialists, etc.).

Manage and coordinate external crowdsourced collectors and third‑party data service vendors, tracking key performance indicators (KPIs).

Cross‑Functional Collaboration

Work closely with hardware R&D, algorithm teams, product departments, and the broader BD department to co‑define data collection specifications and standards.

Act as the operational interface between clients and R&D teams, precisely understanding requirements to ensure datasets are delivered on time and with high quality.

Assist in managing regional operational budgets, ensuring all data collection and processing activities strictly comply with US data privacy, security, and relevant regulations.

Job Requirements
  • Educational Background: Bachelor’s degree or above. Majors in Computer Science, Communications, Automation, Data Science, Management, or related fields are preferred.
  • Core Experience: 3+ years of experience in supply chain, BD, operations, project management, or data management, including at least 1 year of team management experience. Those with a certain understanding of or practical experience in crowdsourcing models or the sharing economy are preferred; backgrounds in crowdsourced operations within ride‑hailing, local on‑demand services, or the AI data sector are highly preferred.
  • Crowdsourcing & Rollout Expertise: Hands‑on experience in crowdsourcing models, the sharing economy, or managing large‑scale localized rollouts and promotional campaigns is required. Backgrounds in crowdsourced operations within ride‑hailing, local on‑demand services, or the AI data sector are highly preferred.
  • Scenario Expansion Capability: Possess awareness of supply chain and scenario expansion, and understand the operational characteristics of at least one real‑world scenario (e.g., households, factories, retail, etc.).
  • Technical Understanding: Ability to understand the basic technical requirements of embodied AI data collection. Familiarity with sensors, data formats, and collection specifications is preferred.
  • Execution & Responsibility: Ability to go deep into the frontline to solve practical operational problems, possessing a strong sense of responsibility and determination to achieve goals.
  • Communication & Collaboration: Excellent cross‑departmental and cross‑team communication and coordination skills, with the ability to effectively manage and motivate small teams.
  • Language Skills: Excellent verbal and written communication skills in English. Proficiency in Spanish is a major plus for engaging with local communities and external teams.
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