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Freelance Machine Learning Data Annotation Jobs in Saint Augustine, FL

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Following the machine learning lifecycle, the data scientist should be able to convert the results into actionable product recommendations to present internally and externally. They will lead ...

Following the machine learning lifecycle, the data scientist should be able to convert the results into actionable product recommendations to present internally and externally. They will lead ...

We are looking for aMLOps Engineerto join our team and contribute to developing robust data solutionsto support our Machine Learning,Data Science, Data Engineering and Software Engineering. Position ...

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Freelance Machine Learning Data Annotation information

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$11

$19

$30

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

As of Aug 19, 2026, the average hourly pay for freelance machine learning data annotation in Saint Augustine, FL is $19.07, 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 Saint Augustine, FL look for?

The top searched job categories for Freelance Machine Learning Data Annotation jobs in Saint Augustine, FL are:

What cities near Saint Augustine, FL are hiring for Freelance Machine Learning Data Annotation jobs?

Cities near Saint Augustine, FL with the most Freelance Machine Learning Data Annotation job openings:

Spanish Data Annotator Specialist (Based in NY)

Welo Data

Jacksonville, FL

$28/hr

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 20 days ago


Job description

OVERVIEW

We are seeking a QA Analyst - Data Annotation Specialist to contribute to a high-profile technology project. The ideal candidate will have a foundational understanding of quality assurance, data annotation, and data handling. Additionally, they must be fully proficient in English (U.S.) and Spanish (Spain) and possess excellent communication skills. They will play a pivotal role in ensuring the quality and accuracy of the project data.

Project Details

Job Title: QA Analyst - Data Annotation Specialist

Location: On-site at one of our offices office in South Bay, CA (Menlo Park or Sunnyvale)

Hours: 40 hours weekly

Language: Spanish (Spain)

Start date: Mid-January 2025

Employment Type: W-2 Contract

Duration: At least 12 months (with potential for extension)

Pay rate: $28/Hour

Must have valid work authorization in the US (We do not sponsor VISAs at this time)

Responsibilities

    • Conduct data annotation and QA
    • Collaborate with team members on-site
    • Ensure secure handling of data and maintain confidentiality

Requirements

    • Proficiency in English (US) and Spanish (Spain) at a fully fluent level is required.
    • At least 1-2 years of data annotation experience
    • Visual annotation experience is a plus (Video & Image)
    • Experience in quality assurance
    • Excellent communication skills
    • Augmented Reality experience is a plus
    • No technical skills needed, but a linguistic background and/or formal QA experience is required
    • Ability to work 100% on-site
    • Strong attention to detail and problem-solving skills

Benefits

    • Paid Sick Time
    • Employee Assistance Program  
    • Following eligibility requirements: Medical Insurance
    • Dental Insurance
    • Vision Insurance
    • HSA
    • Voluntary Life Insurance
    • Accident, Critical Illness, Hospital Indemnity Insurance
    • 401(k) Retirement Plan

$28 - $28 an hour

Please note that in order to verify work authorization as is required by Federal law (I-9 process), all new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment.

To know more details (Click here)

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.  In addition, we employ anti-fraud checks to ensure all candidates meet the requirements of the program.

As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.


Working at Welo Data

What to expect from working at Welo Data

From Welo Data

About Welo Data, in their own words

From Welo Data

Welo Data is a global AI data services company powering the next generation of AI. We build, annotate, and validate the training datasets that make AI models accurate, safe, and ready for the real world — across languages, cultures, and domains.

Our team of experts spans the globe, combining deep technical knowledge with a human-centered approach. If you want your work to shape how AI understands the world, you'll find your place here.

Diversity and inclusion statement

From Welo Data

Our Strength is derived from Winning Together. Welo Data is unequivocally committed to developing and fostering a workplace and organizational culture that values the diversity of thought and perspective delivered by a diverse global workforce operating within an inclusive organization.