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Freelance Machine Learning Data Annotation Jobs in Norman, OK

Americanfidelity

Data Scientist

Oklahoma City, OK · Hybrid

Work with large, complex data sets using to solve difficult, non-routine analysis problems ... Research and engineer analysis, forecasting, machine learning, deep learning, neural networks ...

ANAUTICS INC

Senior Data Scientist

Oklahoma City, OK · On-site

$100 - $130/hr

Build statistical, machine learning, and decision models that help teams understand complex operations and act with confidence. Impact * Turn messy operational data into trusted signals. * Develop ...

mytfcuhr

Data Engineer I,II,III, SR

Oklahoma City, OK · On-site

$106K - $133K/yr

A master's degree in computer science, information systems, computer engineering, artificial intelligence, machine learning, data science, or a closely related field is preferred at the Senior level.

Sabai Global

Operational Data Analyst

Oklahoma City, OK · On-site

$60 - $80/hr

Perform dataset collection for creation of new machine learning processes * Perform data labelling and dataset refinement to fine-tune current and future machine learning methods * Manage and resolve ...

micro1 AI

AI Trainer - Microbiology Expert

Edmond, OK · Remote

$70 - $90/hr

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

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Freelance Machine Learning Data Annotation information

See Norman, OK salary details

$11

$19

$30

How much do freelance machine learning data annotation jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for freelance machine learning data annotation in Norman, OK is $19.10, according to ZipRecruiter salary data. Most workers in this role earn between $15.10 and $21.83 per hour, depending on experience, location, and employer.

What is freelance machine learning data annotation?

Freelance machine learning data annotation involves labeling or tagging data—such as images, text, audio, or video—to help train machine learning models. As a freelancer, you work independently or through platforms, completing specific annotation tasks assigned by companies or researchers. This work is essential because high-quality labeled data is required for AI systems to learn and make accurate predictions. Annotators may categorize images, transcribe speech, or highlight relevant information in documents. The flexibility of freelancing allows you to choose projects and work remotely.

What are the key skills and qualifications needed to thrive as a freelance machine learning data annotation specialist?

To thrive as a Freelance Machine Learning Data Annotation specialist, you need attention to detail, basic knowledge of data labeling concepts, and familiarity with machine learning data types. Experience with annotation tools (such as Labelbox, RectLabel, or CVAT) and understanding of data privacy protocols are commonly required. Strong communication, time management, and the ability to follow complex guidelines are essential soft skills for delivering accurate results. These skills ensure high-quality, consistent data annotation, which is critical for effective machine learning model training and performance.

What are some common challenges faced by freelance machine learning data annotators, and how can they be managed?

Freelance machine learning data annotators often encounter challenges such as maintaining data accuracy, handling repetitive tasks, and understanding complex annotation guidelines. Staying organized and regularly reviewing project instructions can help ensure consistency and quality in annotations. Additionally, communicating proactively with project managers and utilizing annotation tools efficiently can help manage workload and clarify uncertainties. Building expertise in different data types (text, image, audio) also allows annotators to diversify their projects and reduce monotony.

What is the difference between Freelance Machine Learning Data Annotation vs Data Labeler?

AspectFreelance Machine Learning Data AnnotationData Labeler
CredentialsBasic understanding of annotation tools, sometimes with specialized domain knowledgeTypically no formal credentials required
Work EnvironmentRemote, flexible, project-basedOften remote or in-house, depending on employer
Industry UsageUsed in AI/ML development for training datasetsUsed in data preparation for various industries, including AI
Search/Comparison IntentFocuses on freelance opportunities, project scope, and toolsMore general, often employed by companies for data labeling tasks

Freelance Machine Learning Data Annotation involves independently completing annotation tasks for AI models, often with specialized tools and domain knowledge. Data Labelers typically perform similar tasks but may work as employees or contractors within a company. The main difference lies in the freelance nature and project-based work of data annotation roles.

Can I work for freelance machine learning data annotation with no experience?

Freelance machine learning data annotation jobs often do not require prior experience, as many tasks involve simple labeling or categorization that can be learned quickly. Basic computer skills, attention to detail, and familiarity with annotation tools are helpful, and training is usually provided. However, building a portfolio or gaining some familiarity with data annotation platforms can improve job prospects.

What job categories do people searching Freelance Machine Learning Data Annotation jobs in Norman, OK look for?

The top searched job categories for Freelance Machine Learning Data Annotation jobs in Norman, OK are:

Freelance Machine Learning Data Annotation jobs near you

Data Scientist

Americanfidelity

Oklahoma City, OK • Hybrid

Full-time

Posted 22 days ago

Job description

Job Description:

Work with large, complex data sets using to solve difficult, non-routine analysis problems, applying advanced analytical methods as needed to complete end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.

Engineer analysis pipelines iteratively to provide insights at scale. Develop comprehensive understanding of data structures and metrics, advocating for changes where needed in systems, products and processes.

Research and engineer analysis, forecasting, machine learning, deep learning, neural networks, artificial intelligence and optimization methods to improve the quality of products; example application areas include customer segmentation modeling and end-user behavioral modeling/prediction.

Technical Skills and Requirements:

  • Expert in multiple statistical software (e.g., R, Python, Julia, MATLAB, pandas) and associated data science libraries (scikit-learn).
  • Expert in database languages (e.g., SQL).
  • Experience creating meaningful data visualizations and/or interactive dashboards that communicate findings and business impacts using platforms such as Tableau, Qlik, Power BI, RShiny, plotly, and d3.js.
  • Applied experience with machine learning on large datasets using Big Data tools such as Apache's Hadoop or Spark
  • Expert in deep learning techniques and neural networks using languages such as as TensorFlow
  • Expert in multiple major programming language (C/C++. C#, Java, Python, etc.) or optimization modeling languages (AMPL, GAMS, AIMMS, OPL, etc.)
  • Experience with data science methods related to data architecture, data cleaning, data and feature engineering, and predictive analytics.
  • Strong background in modeling large scale discrete, nonlinear or stochastic mathematical optimization models and engineering efficient optimization algorithms.
  • Familiarity with natural language processing, machine learning, statistical modeling, predictive modeling, and hypothesis testing.
  • Familiarity working with both structured and unstructured data, including textual data.
  • Ability to work in a fast-paced environment.
  • Exceptionally strong communication skills, including written, verbal and listening which can be deployed successfully when addressing entry level Colleagues to management to senior executives. This includes the ability to speak confidently in both business and technological surroundings and appropriately transliterate between the two.
  • Exceptional analytical thinking and problem solving skills.
  • Exceptional understanding of business and business strategy.
  • Exceptional planning skills.
  • Exceptional organizational skill and ability to work autonomously.

Education:

Master's degree in related field required.

Location:

This is a hybrid position. Applicants must be located in OKC Metro area or willing to relocate.

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