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Annotation Labelling Jobs in California (NOW HIRING)

Figure

Data Quality Partner Lead

San Jose, CA

$120K - $180K/yr

Direct experience managing data annotation, labeling, or content review vendors * Background at a frontier AI lab, autonomous vehicle company, or other organization where data quality at scale was a ...

Figure AI

Data Quality Partner Lead

San Jose, CA

$120K - $180K/yr

Direct experience managing data annotation, labeling, or content review vendors * Background at a frontier AI lab, autonomous vehicle company, or other organization where data quality at scale was a ...

Figure

Data Quality Partner Lead

San Jose, CA · On-site

$120K - $180K/yr

Direct experience managing data annotation, labeling, or content review vendors * Background at a frontier AI lab, autonomous vehicle company, or other organization where data quality at scale was a ...

xAI

Internal Tools (Front-End)

Palo Alto, CA · On-site

$180K - $440K/yr

Starfleet - Our Human Data Collection Platform (large-scale annotation, labeling, quality control, and human feedback systems) * Toolbox - Our unified Research Platform for model training ...

Tesla

Technical Program Manager, Tesla AI

Palo Alto, CA · On-site

$151.80K - $196.50K/yr

Responsibilities : • Lead end-to-end program management for Tesla AI initiatives spanning data collection, annotation/labeling pipelines, and new vehicle programs • Define and maintain program ...

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Annotation Labelling information

What are the key skills and qualifications needed to thrive as an Annotation Labelling Specialist, and why are they important?

To thrive as an Annotation Labelling Specialist, you need strong attention to detail, data analysis capabilities, and familiarity with data annotation standards, usually supported by a background in computer science or related fields. Proficiency with annotation tools such as Labelbox, CVAT, or Supervisely, and sometimes knowledge of basic programming or scripting, is typically required. Excellent communication, consistency, and the ability to follow complex instructions are crucial soft skills for producing high-quality labeled data. These skills ensure the accuracy and reliability of datasets, which are foundational for successful machine learning and AI model development.

What are some common challenges faced by Annotation Labelling professionals, and how can they be managed?

Annotation Labelling professionals often encounter challenges such as maintaining high accuracy while handling repetitive data, meeting tight deadlines, and adapting to evolving project guidelines. To manage these, it’s important to develop strong attention to detail, regularly communicate with team leads to clarify instructions, and leverage annotation tools efficiently. Collaborating closely with quality assurance teams can also help identify and correct errors early, ensuring consistently high-quality outputs.

What is annotation labelling?

Annotation labelling is the process of tagging or marking data—such as images, text, or audio—with relevant information or labels. This is an essential step in preparing datasets for machine learning and artificial intelligence models, as it helps algorithms understand and learn from raw data. Annotation labelling can include tasks like identifying objects in photos, transcribing speech, or categorizing text. Skilled annotators ensure accuracy and consistency to improve model performance. People in this role often use specialized tools or software to streamline and standardize the annotation process.

What is the difference between Annotation Labelling vs Data Labeling Specialist?

AspectAnnotation LabellingData Labeling Specialist
CredentialsBasic technical skills, attention to detailSimilar skills, sometimes additional domain knowledge
Work EnvironmentData annotation platforms, remote or officeData annotation tasks, often remote or in-office
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, healthcare, retail
Search & ComparisonCommonly compared for entry-level data tasksRelated but broader role

Annotation Labelling involves marking data such as images, text, or videos to train AI models. Data Labeling Specialists perform similar tasks but may have a broader scope, including verifying and managing labeled data. Both roles are essential in AI development, often overlapping in skills and work environment, but Annotation Labelling is more focused on the annotation process itself.

What are popular job titles related to Annotation Labelling jobs in California? For Annotation Labelling jobs in California, the most frequently searched job titles are:
What job categories do people searching Annotation Labelling jobs in California look for? The top searched job categories for Annotation Labelling jobs in California are:
What cities in California are hiring for Annotation Labelling jobs? Cities in California with the most Annotation Labelling job openings:
Annotation Labelling jobs near you
Data Quality Partner Lead

Data Quality Partner Lead

Figure

San Jose, CA

$120K - $180K/yr

Other

Posted 27 days ago

Job description

Figure is an AI Robotics company developing a general purpose humanoid. Our Humanoid is designed for corporate tasks targeting labor shortages and jobs that are undesirable or unsafe. We are based in San Jose, CA and require 5 days/week in-office collaboration.

We are looking for a Data Quality Partner Lead to build Figure's external annotation and review vendor network from scratch. You will source, evaluate, onboard, and manage the BPOs, specialized labeling firms, and crowdsourcing platforms that extend our data quality capacity.

Responsibilities:

  • Own Figure's external annotation and review vendor strategy end to end, from sourcing through onboarding through ongoing performance management
  • Build the vendor pipeline from zero by identifying and engaging BPOs, specialized labeling firms, crowdsourcing platforms, and emerging providers in the AI data ecosystem
  • Run structured evaluations of prospective vendors, including pilots, quality benchmarking, and capacity testing, and make clear recommendations on who to scale with
  • Translate the Data Quality team's standards and methodologies into vendor specs, making sure the bar we set internally is the bar our partners deliver against
  • Stand up the operating model for managing partners at scale, including scorecards, escalation paths, and the tooling

Requirements:

  • 5+ years in vendor management, BPO/outsourcing partnerships, strategic sourcing, or operations roles with significant external partner ownership
  • Track record of building or scaling a vendor function from an early stage, ideally in a domain where quality was the primary lever
  • Comfortable rapidly building and deploying apps/agents using AI coding tools to build internal tools, dashboards, and trackers (zero technical academic background necessary)
  • Excellent written and verbal communication skills, especially when setting expectations with external partners
  • Comfortable operating with ambiguity and managing multiple concurrent partner relationships
  • Low ego, team player with can-do attitude

Bonus Qualifications:

  • Direct experience managing data annotation, labeling, or content review vendors
  • Background at a frontier AI lab, autonomous vehicle company, or other organization where data quality at scale was a core problem
  • A passion for helping scale the deployment of learning humanoid robots

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.

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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