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Ai Data Labeling Jobs in California (NOW HIRING)

Figure

Lead, Data Quality - Partnerships

San Jose, CA · On-site

$120K - $180K/yr

Experience scaling a multi-vendor or multi-region labeling operation. * Experience with golden set / ground truth construction. * Background in robotics, autonomous systems, LLM, or physical AI data.

Figure

Lead, Data Quality - Partnerships

San Jose, CA · On-site

$120K - $180K/yr

Experience scaling a multi-vendor or multi-region labeling operation. * Experience with golden set / ground truth construction. * Background in robotics, autonomous systems, LLM, or physical AI data.

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Ai Data Labeling information

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How much do ai data labeling jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for ai data labeling in California is $46.29, according to ZipRecruiter salary data. Most workers in this role earn between $17.42 and $68.50 per hour, depending on experience, location, and employer.

What is an AI data labeling?

An AI Data Labeling job involves annotating or tagging data (such as images, text, audio, or video) to train machine learning models. Labelers categorize, classify, or highlight data based on specific guidelines to help AI understand patterns and make accurate predictions. This process is crucial for supervised learning, where models learn from labeled examples. AI Data Labeling jobs are common in industries like healthcare, finance, and autonomous vehicles. Attention to detail and consistency are key skills for success in this role.

What are the key skills and qualifications needed to thrive in AI data labeling?

To thrive as an AI Data Labeling professional, you need strong attention to detail, analytical thinking, and the ability to follow precise guidelines, typically backed by a high school diploma or higher. Familiarity with annotation tools such as Labelbox, Supervisely, or internal labeling platforms, as well as basic understanding of data privacy practices, is often required. Patience, reliability, and good communication skills are important soft skills for consistently delivering high-quality labeled datasets and working effectively with team members. These skills ensure accurate data preparation for training AI models, directly impacting the model’s performance and the success of machine learning projects.

What does an AI data labeling do?

As an AI Data Labeling professional, your primary responsibilities include reviewing raw images, audio, or text data and accurately tagging or classifying them based on set guidelines provided by your employer. You may also be required to flag ambiguous cases or data anomalies and provide feedback to improve labeling instructions. Collaboration with data scientists or machine learning engineers is common to ensure your work aligns with project needs. Maintaining high accuracy while meeting productivity goals is essential for success in this role.

What are the most commonly searched types of Ai Data Labeling jobs in California? The most popular types of Ai Data Labeling jobs in California are:
What are popular job titles related to Ai Data Labeling jobs in California? For Ai Data Labeling jobs in California, the most frequently searched job titles are:
What job categories do people searching Ai Data Labeling jobs in California look for? The top searched job categories for Ai Data Labeling jobs in California are:
What cities in California are hiring for Ai Data Labeling jobs? Cities in California with the most Ai Data Labeling job openings:
Ai Data Labeling jobs near you
Infographic showing various Ai Data Labeling job openings in California as of August 2026, with employment types broken down into 56% Full Time, 33% Part Time, and 11% Contract. Highlights an 72% In-person, and 28% Remote job distribution, with an average salary of $96,286 per year, or $46.3 per hour.

Lead, Data Quality - Partnerships

Figure

San Jose, CA • On-site

$120K - $180K/yr

Full-time

Posted 28 days ago

Job description

Figure is an AI robotics company developing autonomous general-purpose humanoid robots. The goal of the company is to ship humanoid robots with human level intelligence. Its robots are engineered to perform a variety of tasks in the home and commercial markets. Figure is headquartered in San Jose, CA.
We are building the data foundation that powers our humanoid robots. The Data Quality team owns the standards, guidelines, and audit infrastructure that ensure our training data meets the bar our AI systems require. As we scale, a growing share of that work runs through external vendors, and this role owns those relationships end to end.
As External Partnerships Lead, you'll own Figure's external data vendor portfolio for Data Quality: who we work with, what we hold them to, and how their output meets the same bar as our in-house team. You'll source and select vendors, negotiate the commercials, set and enforce SLAs, and stand up the calibration and audit processes that keep external work on standard. When a project rotates to external support, you are the senior owner of that delivery, and the Project Coordinators on it work through you.
Responsibilities:
  • Own the full external vendor portfolio for Data Quality: sourcing, evaluation, onboarding, and offboarding of data labeling and review partners.
  • Negotiate commercial terms, statements of work, and contracts, and manage pricing, budgets, and surge capacity across vendors.
  • Set and enforce SLAs and acceptance criteria; hold every vendor to the same golden set and audit bar as the in-house team.
  • Serve as the senior owner when a project rotates to external support, directing the Project Coordinators running that work.
  • Build and run the vendor scorecard: throughput, quality, inter-annotator agreement, and SLA adherence, reviewed in regular business reviews.
  • Stand up calibration exercises and golden set checks with each vendor so external output matches internal standards.
  • Partner with engineering and ML stakeholders to translate data quality requirements into vendor-ready guidelines and specs.
  • Plan capacity and ramp with vendors to meet project timelines, including surge needs and new regions.
  • Coordinate with internal Project Coordinators and leadership on which projects rotate to which vendors and when.

Requirements:
  • 6+ years in data quality, data labeling operations, vendor or partner management, or ML data operations, with end-to-end ownership of vendor relationships or major workstreams.
  • Direct experience selecting, contracting, and managing external data vendors, including defining and enforcing SLAs.
  • A track record negotiating commercial terms (pricing, SOWs, capacity) and running vendor business reviews.
  • Experience setting quality standards, acceptance criteria, and audit or calibration processes that external teams executed against.
  • Comfort working with engineering and ML stakeholders to translate technical requirements into operational guidance.
  • Leadership across people you both do and do not directly manage, including coordinators running work on your vendors.

Bonus Qualifications:
  • Experience scaling a multi-vendor or multi-region labeling operation.
  • Experience with golden set / ground truth construction.
  • Background in robotics, autonomous systems, LLM, or physical AI data.
  • Experience standing up new vendor operations in international or lower-cost markets.

The US base salary range for this full-time position is between $120,000 - $180,000 annually.
The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

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