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Annotation Jobs (NOW HIRING)

Sunday

Data Annotation Lead

Redwood City, CA · On-site

Responsibilities : • Build a data annotation team • Manage the people side of data annotations • Create documentation • Be in the weeds and annotate data yourself anytime something new is ...

Recruitment Room

$20/hr

Data Annotation Generalist Contract Type: Hourly, Independent Contractor Location: Remote Compensation: $20 per hour Openings: 600 Role Overview We are seeking detail-oriented Data Annotation ...

Sunday Inc

Data Annotation Lead

Redwood City, CA · On-site

This role is about building and leading a world class in-house data annotation team that is able to pivot quickly to any research experiment while delivering on quality, quantity, and variety when it ...

Bot Auto

Data Annotation Specialist

Houston, TX · On-site

The Data Annotation Specialist will be responsible for creating, refining, and validating ground-truth data for the company's perception and mapping stacks. Responsibilities : • 3D Perception ...

Bot Auto

Data Annotation Specialist

Houston, TX

Role Overview We are seeking a highly meticulous and motivated Data Annotation Specialist to join our team. High-quality data is the lifeblood of our "Physical AI" and the foundation of our ...

Bot Auto

Data Annotation Specialist

Houston, TX · On-site

Role Overview We are seeking a highly meticulous and motivated Data Annotation Specialist to join our team. High-quality data is the lifeblood of our "Physical AI" and the foundation of our ...

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How much do annotation jobs pay per year?

As of Jul 7, 2026, the average yearly pay for annotation in the United States is $58,415.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,500.00 and $58,000.00 per year, depending on experience, location, and employer.

What is an Annotation job?

An annotation job involves labeling or tagging data, such as text, images, audio, or video, to help train artificial intelligence and machine learning models. Annotators manually or semi-automatically add metadata, such as identifying objects in images, transcribing speech, or categorizing text. This process improves AI accuracy by providing high-quality training data. Annotation work is crucial for industries like autonomous driving, healthcare, and natural language processing.

What does an annotation job do?

An annotation job involves labeling or tagging data, such as images, text, or videos, to help train machine learning models. Workers typically use specialized tools to add accurate annotations, which are essential for developing AI systems in fields like computer vision and natural language processing.

Which 5 jobs will survive AI?

Annotation jobs, which involve labeling data for machine learning, are likely to persist as they require human judgment and domain expertise. Roles such as data annotators, quality assurance specialists, and domain-specific annotators will continue to be essential, especially in areas needing nuanced understanding and accuracy. Skills in critical thinking and familiarity with annotation tools will support job stability in this field.

What are the key skills and qualifications needed to thrive in the Annotation position, and why are they important?

Excelling in an Annotation role generally requires keen attention to detail, strong analytical abilities, and a high level of accuracy, often backed by a relevant educational background. Familiarity with annotation tools, data labeling software, and sometimes basic programming or data management platforms is valuable. Effective time management, consistency, and clear communication are soft skills that differentiate top performers. These competencies are crucial to ensuring data quality and supporting the development of machine learning and AI systems.

How much do annotators make?

Annotators typically earn between $10 and $20 per hour, depending on the complexity of the task, experience, and the employer. Many work remotely and may be paid per task or project rather than hourly, with some platforms offering bonuses for high accuracy or speed.

Is data annotation real or fake?

Data annotation is a legitimate job that involves labeling data such as images, text, or videos to train machine learning models. It requires attention to detail and familiarity with annotation tools, and it is widely used in AI development across various industries.

What are the typical projects or tasks an Annotation specialist works on throughout the week?

Annotation specialists typically work on projects involving the labeling and categorizing of data—such as images, videos, audio, or text—to train machine learning models. Weekly tasks may include reviewing raw data, applying specific tagging guidelines, performing quality checks on completed annotations, and collaborating with team members or machine learning engineers to ensure accuracy and consistency. Frequent feedback sessions and ongoing updates to annotation instructions are common as project requirements evolve. This role often requires close teamwork and clear communication within a collaborative environment, especially for large-scale or rapidly changing projects.

More about Annotation jobs
What cities are hiring for Annotation jobs? Cities with the most Annotation job openings:
What are the most commonly searched types of Annotation jobs? The most popular types of Annotation jobs are:
What states have the most Annotation jobs? States with the most job openings for Annotation jobs include:
What job categories do people searching Annotation jobs look for? The top searched job categories for Annotation jobs are:
Annotation jobs near you
Infographic showing various Annotation job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 34% Full Time, 31% Part Time, and 34% Contract. Highlights an 34% Physical, and 66% Remote job distribution, with an average salary of $58,415 per year, or $28.1 per hour.
Data Annotation Lead

Data Annotation Lead

Physical Intelligence

San Francisco, CA • On-site

Full-time

Posted 7 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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