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Full Time Ai Data Annotation Jobs in California (NOW HIRING)

Sunday

Data Annotation Lead

Redwood City, CA · On-site

... data annotation • Ability to leverage AI to help improve productivity Company : Sunday is a robotics and artificial intelligence company that develops an autonomous home robot to assist with ...

Sunday Inc

Data Annotation Lead

Redwood City, CA · On-site

Build a data annotation team * Own annotation operations end-to-end * Manage the people side of ... Ability to leverage AI to help improve productivity At Sunday Robotics, we're building technology ...

Tiki AI

AI Data Software Engineer

San Francisco, CA · On-site

$134K - $162K/yr

Tiki AI provides end-to-end data annotation and intelligence solutions that transform raw information into high-quality, actionable datasets. Founded in , the company is headquartered in San ...

Abaka AI

Data Solutions Engineer

Mountain View, CA · On-site

$136K - $163K/yr

Abaka AI provides accurate and efficient AI data services, including data collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is headquartered in Palo Alto, USA ...

Sunday

Technical Program Manager, Data Engine

Redwood City, CA · On-site

$157K - $204K/yr

... AI labs/data vendors • Technical skills to build tools for data annotation or collection • Ability to leverage AI to help improve productivity Company : Sunday is a robotics and artificial ...

Abaka AI

Data Solutions Engineer

Mountain View, CA · On-site

$136K - $163K/yr

Abaka AI provides accurate and efficient AI data services, including data collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is headquartered in Palo Alto, USA ...

Abaka AI

Data Solutions Engineer

Mountain View, CA · On-site

$136K - $163K/yr

Abaka AI provides accurate and efficient AI data services, including data collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is headquartered in Palo Alto, USA ...

Abaka AI

Data Operations Engineer

Mountain View, CA · On-site

$136K - $163K/yr

Abaka AI provides accurate and efficient AI data services, including data collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is headquartered in Palo Alto, USA ...

Abaka AI

Data Operations Engineer

Mountain View, CA · On-site

$136K - $163K/yr

Abaka AI provides accurate and efficient AI data services, including data collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is headquartered in Palo Alto, USA ...

Abaka AI

Data Operations Engineer

Mountain View, CA · On-site

$136K - $163K/yr

Abaka AI provides accurate and efficient AI data services, including data collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is headquartered in Palo Alto, USA ...

Figure

Helix AI Engineer, Data Infrastructure

San Jose, CA · On-site

$126K - $165K/yr

... full-time experience building reliable backend systems • Experience with Linux and command line ... data annotation and dataset management tools. Company : Figure is an AI robotics company that ...

Figure

Helix AI Engineer, Data Infrastructure

San Jose, CA · On-site

$126K - $165K/yr

... full-time experience building reliable backend systems • Experience with Linux and command line ... data annotation and dataset management tools. Company : Figure is an AI robotics company that ...

Figure

Helix AI Engineer, Data Infrastructure

San Jose, CA · On-site

$126K - $165K/yr

... full-time experience building reliable backend systems • Experience with Linux and command line ... data annotation and dataset management tools. Company : Figure is an AI robotics company that ...

Figure

Helix AI Engineer, Data Infrastructure

San Jose, CA · On-site

$126K - $165K/yr

... full-time experience building reliable backend systems • Experience with Linux and command line ... data annotation and dataset management tools. Company : Figure is an AI robotics company that ...

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All JobsAi Data Annotation JobsFull Time Ai Data Annotation JobsFull Time Ai Data Annotation Jobs in California

Full Time Ai Data Annotation information

What are some common challenges faced by full time AI data annotation professionals, and how can they be addressed?

AI Data Annotation professionals often encounter challenges such as maintaining high accuracy while working with large datasets, interpreting ambiguous data, and consistently following complex labeling guidelines. These challenges can be addressed through thorough training, frequent communication with project managers or data scientists, and utilizing annotation tools with built-in quality checks. Collaboration with team members and regular feedback sessions also help ensure consistency and improve overall data quality, making the annotation process smoother and more efficient.

What are the key skills and qualifications needed to thrive as a full time AI data annotation specialist?

To thrive as a Full Time AI Data Annotation Specialist, you need strong attention to detail, basic data literacy, and often a high school diploma or equivalent. Familiarity with annotation platforms (like Labelbox or Supervisely) and understanding of data labeling guidelines are typically required. Patience, consistency, and effective communication are soft skills that help ensure accuracy and clarity in collaborative projects. These skills and qualities are crucial for producing high-quality labeled data, which directly impacts the performance of AI models.

What is a full time AI data annotation job?

Full Time AI Data Annotation jobs involve labeling, tagging, or categorizing data such as images, text, audio, or video to help train machine learning models. Annotators play a crucial role in ensuring AI systems understand and process information accurately by providing high-quality, human-curated data. These positions usually require attention to detail, basic computer skills, and the ability to follow specific guidelines for different projects. Full-time roles typically offer stable hours and may be remote or on-site, depending on the employer.

What is the difference between Full Time Ai Data Annotation vs Data Labeler?

AspectFull Time Ai Data AnnotationData Labeler
CredentialsHigh school diploma or equivalent; some roles prefer basic technical skillsHigh school diploma or equivalent; minimal technical requirements
Work EnvironmentOffice or remote; part of AI development teamsOffice or remote; often task-based or freelance
Industry UsageUsed across AI, machine learning, and data science industriesPrimarily in AI and machine learning industries for data preparation
Job ScopeFull-time, with responsibilities including data annotation, quality control, and collaborationTask-specific, focusing on labeling data accurately for AI training

Full Time Ai Data Annotation roles typically require more consistent hours, team collaboration, and a broader scope of responsibilities compared to Data Labelers, who often work on individual tasks with minimal oversight. Both roles are essential in AI development, but Full Time Ai Data Annotation offers more stability and integration within AI projects.

What are the most commonly searched types of Ai Data Annotation jobs in California? The most popular types of Ai Data Annotation jobs in California are:
What are popular job titles related to Full Time Ai Data Annotation jobs in California? For Full Time Ai Data Annotation jobs in California, the most frequently searched job titles are:
What job categories do people searching Full Time Ai Data Annotation jobs in California look for? The top searched job categories for Full Time Ai Data Annotation jobs in California are:
What cities in California are hiring for Full Time Ai Data Annotation jobs? Cities in California with the most Full Time Ai Data Annotation job openings:
Full Time Ai Data Annotation jobs near you
Infographic showing various Full Time Ai Data Annotation job openings in California as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 71% Physical, 3% Hybrid, and 26% Remote job distribution.

Data Annotation Lead

Physical Intelligence

San Francisco, CA • On-site

Full-time

Re-posted 5 days ago

Job description

Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.
The role
We're looking for a Data Annotation Lead to own annotation operations and scale the team behind it. Annotation is core to how our models improve, and demand is growing fast. You will scale the annotation workforce from 100s to 1,000s while raising the quality bar - designing the org, the training pipeline, the quality system, and the metrics that let it scale efficiently.
You will own the people and the operation: throughput, quality, cost, and delivery across every annotation type.
In this role you will
  • Own annotation operations end-to-end: throughput, quality, cost, and on-time delivery across all annotation types.
  • Scale the annotation workforce from 100s to 1,000s: workforce planning, org design, and the hiring and onboarding funnel.
  • Build and lead a multi-layer management structure; hire, develop, and manage managers and team leads.
  • Scale throughput with autolabeling and model-based annotation: design human-in-the-loop workflows where models pre-label and annotators review, correct, and escalate, so output grows faster than headcount.
  • Stand up the training and certification pipeline that brings new annotators and teams to the quality bar quickly and consistently.
  • Define and continuously raise the quality bar: rubrics, calibration, audit/QA loops, and quality-adjusted productivity.
  • Establish operational metrics and reporting (presence, throughput, acceptance/rejection, rework) and drive week-over-week improvement.
  • Run capacity planning and prioritization against competing demand; allocate teams to the highest-impact work.
  • Manage performance at scale with clear standards, feedback, and a fair improvement/exit process.
  • Partner with product and engineering to define annotation tooling that unlocks throughput and quality.
  • Partner with research and project leads to translate annotation needs into clear instructions, rubrics, and SLAs.
  • Own the in-house vs. vendor mix and manage external partners where used.
  • Own the annotation operating budget and unit economics; improve cost-per-annotation while protecting quality.

What you'll bring
  • 7+ years leading scaled data or annotation operations, including teams in the 100s+.
  • 3+ years as a manager of managers.
  • Track record standing up 0→1 annotation programs.
  • Deep command of annotation best practices, operations, and strategy.
  • Experience integrating autolabeling and model-based annotation into human workflows; building human-in-the-loop pipelines that raise throughput without sacrificing quality.
  • Fluency with operational and quality metrics; data-driven management of large workforces.
  • Strong cross-functional partnership with product, engineering, and research/ML.
  • Clear written and verbal communication; able to set and hold standards across a large, distributed team.
  • Working understanding of ML and why annotation quality drives model performance.

Nice to have
  • Experience in robotics, autonomous vehicles, or frontier-AI data pipelines.
  • Experience managing distributed/global and/or vendor workforces.
  • Built annotation tooling or partnered tightly with a tooling team.
  • Experience training or fine-tuning autolabeling models, or partnering closely with the ML teams that do.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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