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Ai Annotation Writing Jobs (NOW HIRING)

Sunday

Data Annotation Lead

Redwood City, CA · On-site

Required : • Clear written and verbal communication to guide our data annotators • Your ability ... to leverage AI to help improve productivity Company : Sunday is a robotics and artificial ...

Dyna Robotics

Data Annotation Specialist

As a Data Annotation Specialist, you will be pivotal in iterating on our AI system by annotating ... Clear written communication and a collaborative attitude Preferred : • Hands-on experience ...

UnitedHealthcare

Manager of Clinical Annotation - | , |

$91K - $163K/yr

  • Retirement

Contribute to roadmap planning for annotation projects and AI initiatives * Identify opportunities ... Listen Actively * Speak and Write Clearly * Innovation Value: Support Change and Innovation

Sunday Inc

Data Annotation Lead

Redwood City, CA · On-site

Clear written and verbal communication to guide our data annotators * Your ability to manage ... Ability to leverage AI to help improve productivity At Sunday Robotics, we're building technology ...

Innodata Inc.

AI Solutions Engineer

Washington, DC

$75 - $80/hr

Validate AI feature integration end-to-end across storefront, annotation platform, and DataCard write-back during Phase C Must-Have Qualifications: * Bachelor's degree in Computer Science, Machine ...

Innodata Inc.

$75 - $80/hr

Validate AI feature integration end-to-end across storefront, annotation platform, and DataCard write-back during Phase C Must-Have Qualifications: * Bachelor's degree in Computer Science, Machine ...

YO AI Labs

AI Data Scientist - Remote

New York, NY · Remote

Job Title: AI Data Science Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job ... Technical & Report Writing * Content Review & Editing * Data Annotation * Data Interpretation

New

YO AI Labs

AI Finance Expert - Remote

Philadelphia, PA · Remote

$100 - $200/hr

Data Annotation * Problem-Solving * Independent Research * Attention to Detail Preferred ... Excellent written communication and professional editing abilities. * Experience with prompt ...

New

YO AI Labs

AI Finance Expert - Remote

Los Angeles, CA · Remote

$100 - $200/hr

Data Annotation * Problem-Solving * Independent Research * Attention to Detail Preferred ... Excellent written communication and professional editing abilities. * Experience with prompt ...

New

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Ai Annotation Writing information

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How much do ai annotation writing jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for ai annotation writing in the United States is $40.46, according to ZipRecruiter salary data. Most workers in this role earn between $23.56 and $46.39 per hour, depending on experience, location, and employer.

What does an AI annotation writer do?

An AI annotation writer labels and annotates data such as images, videos, or text to help train machine learning models. They use specialized tools and follow guidelines to ensure data accuracy and consistency, often working remotely with flexible schedules.

What is an AI annotation writing?

An AI Annotation Writing job involves labeling, tagging, and annotating text data to help train machine learning models. This can include tasks like identifying sentiment, correcting grammar, or categorizing content. The goal is to provide high-quality data that improves the accuracy of AI systems. Strong language skills, attention to detail, and familiarity with AI concepts are often required for this role.

What are the primary day-to-day responsibilities in AI annotation writing?

In an AI Annotation Writing role, your daily tasks generally include reading and understanding various types of content, applying accurate labels or tags, and sometimes providing written explanations or classifications based on specific project guidelines. You may work individually or as part of a larger annotation team, often collaborating with data scientists or project managers to clarify requirements and resolve ambiguous cases. Attention to detail is crucial, as the quality of your annotations directly impacts the performance of the resulting AI models. Projects and content types may vary, offering opportunities to develop expertise in different domains and annotation methods.

What are the key skills and qualifications needed to thrive in AI annotation writing, and why are they important?

To excel in AI Annotation Writing, you should have strong attention to detail, excellent written communication skills, and a good understanding of data labeling concepts, typically supported by experience in content creation or data management. Familiarity with annotation tools like Labelbox, Prodigy, or similar software, as well as basic knowledge of data privacy standards, is often required. Diligence, patience, and the ability to follow detailed guidelines help differentiate top performers in this role. These skills are critical for producing high-quality, accurate labeling data that is foundational to effective AI and machine learning model training.

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Ai Annotation Writing jobs near you
Infographic showing various Ai Annotation Writing job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution, with an average salary of $84,151 per year, or $40.5 per hour.

Data Annotation Lead

Physical Intelligence

San Francisco, CA • On-site

Full-time

Re-posted 15 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.

Apply