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Remote Data Annotation Jobs in Springfield, IL (NOW HIRING)

Remote Data Annotation information

See Springfield, IL salary details

$9

$30

$68

How much do remote data annotation jobs pay per hour?

As of May 28, 2026, the average hourly pay for remote data annotation in Springfield, IL is $30.71, according to ZipRecruiter salary data. Most workers in this role earn between $15.73 and $39.86 per hour, depending on experience, location, and employer.

What is a Remote Data Annotation job?

A Remote Data Annotation job involves labeling, tagging, or categorizing data (such as images, text, audio, or video) to help improve machine learning models. This work is typically done from home using specialized annotation tools provided by employers. Accuracy and attention to detail are essential, as the quality of annotations directly impacts AI model performance. Many companies hire remote annotators on a freelance, part-time, or contractual basis.

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

To thrive as a Remote Data Annotation specialist, strong attention to detail, accuracy, and familiarity with basic data processing concepts are essential, often requiring a high school diploma or equivalent. Experience using data labeling platforms, annotation tools (such as Labelbox or Supervisely), and sometimes familiarity with spreadsheet software may be required. Excellent time management, communication skills, and the ability to work independently are valuable soft skills in this remote role. These skills are vital to ensure that data annotations are consistent, precise, and delivered on schedule, which directly impacts the quality of AI and machine learning outcomes.

What are the typical daily tasks for someone working in Remote Data Annotation?

Daily tasks for a Remote Data Annotation role usually involve reviewing and labeling large volumes of data—such as images, audio clips, text, or video—according to specific project guidelines. You will use specialized annotation tools to identify objects, transcribe content, categorize information, or tag relevant features to support machine learning projects. Communication with project managers or quality assurance teams may be necessary for feedback and clarity on guidelines. Most roles also require regular self-checks for accuracy and the ability to meet productivity quotas or deadlines. This structure allows for a combination of focused individual work and occasional team collaboration to ensure project goals are met.
What are popular job titles related to Remote Data Annotation jobs in Springfield, IL? For Remote Data Annotation jobs in Springfield, IL, the most frequently searched job titles are:
What job categories do people searching Remote Data Annotation jobs in Springfield, IL look for? The top searched job categories for Remote Data Annotation jobs in Springfield, IL are:
What cities near Springfield, IL are hiring for Remote Data Annotation jobs? Cities near Springfield, IL with the most Remote Data Annotation job openings:
Infographic showing various Remote Data Annotation job openings in Springfield, IL as of May 2026, with employment types broken down into 1% As Needed, 89% Full Time, and 10% Part Time. Highlights an 40% Hybrid, and 60% Remote job distribution, with an average salary of $63,870 per year, or $30.7 per hour.
Remote AI Mathematics Expert Train & Evaluate Bots

Remote AI Mathematics Expert Train & Evaluate Bots

DataAnnotation

Springfield, IL • Remote

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

A data annotation company is seeking an advanced mathematician for a remote role to train AI models. Responsibilities include providing complex mathematical problems to AI chatbots and evaluating model performance for correctness. The ideal candidate should be detail-oriented with expertise in mathematics.

A Master's or PhD is preferred but not required, and payment is made via PayPal. This position offers flexibility with project selection and scheduling. #J-18808-Ljbffr