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Ai Annotation Writing Jobs in Pennsylvania (NOW HIRING)

YO AI Labs

Korean Language Expert

Philadelphia, PA · Remote

$65 - $100/hr

... and annotation processes. * Help develop language guidelines and resources tailored to AI training and evaluation. * Participate in regular written and verbal communication to discuss project ...

YO AI Labs

Medical Coder - Remote

Philadelphia, PA · Remote

$50 - $80/hr

Collaborate with project teams through written and verbal communication to improve AI training data ... Familiarity with digital annotation tools or healthcare data projects is a plus. * Commitment to ...

YO AI Labs

Healthcare Attorney - Remote

Philadelphia, PA · Remote

$140 - $400/hr

Provide detailed written feedback to improve AI legal reasoning and content quality. * Identify ... Legal Document Review & Annotation * Policy Analysis * Contract Drafting * U.S. Healthcare ...

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How much do ai annotation writing jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for ai annotation writing in Pennsylvania is $40.55, according to ZipRecruiter salary data. Most workers in this role earn between $23.61 and $46.49 per hour, depending on experience, location, and employer.

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 Pennsylvania as of August 2026, with employment types broken down into 73% Full Time, 25% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $84,353 per year, or $40.6 per hour.

AI Agent Trajectory Annotator and Reviewer

Bespoke Labs

Allentown, PA

$20 - $30/hr

Full-time

Posted 6 days ago

Job description

Type: Contract, hourly

Location: Remote

Hours: 20–30 per week

Pay: $20–30/hour, based on experience and language coverage

Start: Immediate

ABOUT THE ROLE

We evaluate how well advanced AI coding agents solve real engineering problems. An agent is given a real open source codebase inside a container and a hard task, then works on its own for 80 to 250 steps. A trajectory is the full record of that run — every command, result, and decision.

You will do two jobs, and you should expect either on any given day.

•Annotate — Read a trajectory nobody has looked at yet and judge it step by step.

• Review — Take an existing annotation, written by our AI tooling or another person, and confirm, correct, or reject it.

TASKS YOU'LL SEE

• Feature build — Add a working feature to a live library without breaking anything that already worked.

• Rebuild — Work out what a compiled tool does by running it, then rebuild it to match its output, exit codes, and file effects.

• Bug hunt — Find and fix twenty undocumented bugs across a dozen files with no test suite, then record what caused them.

Mostly Python and Go, with some Rust, C, and Ct+. A trajectory runs about 100 steps.

WHAT YOU JUDGE IN A TRAJECTORY

• Was the command right for the state the environment was actually in?

• Did the agent read the previous output correctly?

• Was the step wrong, or only inefficient — these are scored differently.

• Where did the run first go off course — usually earlier than where it visibly broke.

• Did the agent notice its own mistake and recover, or keep building on a false assumption?

• Did it game the grader instead of solving the task (e.g., weakening a test or hardcoding an expected value)?

WHAT WE NEED FROM YOU

• Experience — 2+ years in software engineering, DevOps, or site reliability, with real debugging in real codebases.

• Languages — Strong in Python or Go, and able to read a language you've never used.

• Linux — Comfortable with logs, running processes, build failures, and containers.

• Workflow — Everyday Git, diffs, pull requests, and issue tracking.

• Debugging — Able to work with no test suite and no error message pointing at the cause.

• Focus — Able to hold context across a long run, because step 74 can depend on step 12.

• Writing — Clear English, since every judgement needs an explanation another engineer can check.

Apply