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No Experience Image Annotation Jobs in Iowa (NOW HIRING)

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$10.8K

$59.6K

$76.5K

How much do no experience image annotation jobs pay per year?

As of Sep 3, 2026, the average yearly pay for no experience image annotation in Iowa is $59,568.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,700.00 and $76,000.00 per year, depending on experience, location, and employer.

What is a no experience image annotation?

A No Experience Image Annotation job involves labeling, tagging, or categorizing images to help train AI models, often for machine learning and computer vision applications. These roles typically do not require prior experience, as companies provide guidelines on how to annotate images correctly. The tasks may include drawing bounding boxes, identifying objects, or adding descriptive labels. It is usually a remote or freelance role, making it accessible to beginners looking to enter the AI and data annotation field.

What does a no experience image annotation do?

In a No Experience Image Annotation role, your daily responsibilities typically include labeling images or objects within images according to specific project instructions, reviewing annotated work for accuracy, and occasionally participating in quality checks. You may also provide feedback on annotation challenges or unclear guidelines to your supervisors or team leads. Much of the work is independent and computer-based, though some projects involve collaboration through online communication tools. As you gain experience, you may have opportunities for more complex annotation tasks or to move into quality assurance or project coordination roles. Overall, the role is well-suited for detail-oriented individuals comfortable working independently on repetitive but crucial tasks.

What are the key skills and qualifications needed to thrive in the no experience image annotation position?

To thrive as a No Experience Image Annotation professional, attention to detail, basic computer skills, and the ability to follow guidelines precisely are essential. Familiarity with annotation software or image-labeling platforms is helpful, though most positions provide training and do not require formal certifications. Strong communication, patience, and time management skills help individuals excel in meeting project deadlines and collaborating with remote teams. These abilities ensure high-quality, accurate annotations that are crucial for developing reliable AI and machine learning datasets.

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No Experience Image Annotation jobs near you

AI Agent Trajectory Annotator and Reviewer

Bespoke Labs

Iowa City, IA • On-site

$20 - $30/hr

Full-time

Posted 3 days ago

New

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