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Freelance Amazon Data Annotation Jobs in Maryland

Freelance Amazon Data Annotation information

What is the difference between Freelance Amazon Data Annotation vs Freelance Image Labeler?

AspectFreelance Amazon Data AnnotationFreelance Image Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageE-commerce, AI training datasetsAI training datasets, computer vision projects
Search & Comparison IntentUnderstanding data annotation roles for AmazonComparing image labeling jobs for AI training

Freelance Amazon Data Annotation involves labeling data specifically for Amazon's platform, often focusing on product images, reviews, or metadata. Freelance Image Labeler typically labels images for AI training across various industries. While both roles require attention to detail and remote work, Amazon Data Annotation is more specialized for e-commerce data, whereas Image Labeling covers broader AI applications.

How much do freelance Amazon data annotation jobs pay?

Freelance Amazon data annotation jobs typically pay between $8 and $20 per hour, depending on the complexity of the task, experience, and the platform used. Payments are often project-based or hourly, with some jobs offering bonuses for accuracy or speed. Rates can vary widely based on skill level and the employer's budget.

What are the most commonly searched types of Amazon Data Annotation jobs in Maryland?

The most popular types of Amazon Data Annotation jobs in Maryland are:

What are popular job titles related to Freelance Amazon Data Annotation jobs in Maryland?

For Freelance Amazon Data Annotation jobs in Maryland, the most frequently searched job titles are:

What job categories do people searching Freelance Amazon Data Annotation jobs in Maryland look for?

The top searched job categories for Freelance Amazon Data Annotation jobs in Maryland are:

What cities in Maryland are hiring for Freelance Amazon Data Annotation jobs?

Cities in Maryland with the most Freelance Amazon Data Annotation job openings:

Infographic showing various Freelance Amazon Data Annotation job openings in Maryland as of August 2026, with employment types broken down into 62% Full Time, 23% Part Time, and 15% Contract. Highlights an 23% In-person, and 77% Remote job distribution.

Contractor

Re-posted 2 days ago


Job description

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  • It is 100% onsite position in Woodlawn, MD.<\/b>
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  • Candidate should be local and ready to work on onsite 5 days a week at Client HQ in Woodlawn, MD.<\/b><\/span><\/span><\/span>
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  • Candidate must be able to obtain and maintain a public trust clearance<\/b>
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  • <\/b><\/span><\/span> <\/b><\/span><\/span><\/span>Interviews will be scheduled quickly for early next week. There will only be one round of interview<\/b><\/span><\/span><\/span>
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    Position Description:<\/b><\/span><\/span><\/u>
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    • Hands on experience in Python, NLP frameworks, SQL, Pandas, NLTK, SPACy and LLMs
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    • Well versed in SQL and analyzing trends and transactional data.
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    • Understand real world challenges and develop automated data solutions
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    • Develop, test, and deploy new techniques for NLP understanding
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    • Scalable development\/deployment of ML and Generative AI approaches (such as Large Language Models (LLMs)
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    • Train and optimize NLP\/LLM models and create Python based pipelines
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    • Experience building cloud native solutions on AWS
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    • Determine the nature of analytic problems, evaluate options, and offer recommendations for resolution.
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    • Advise on the methods and data needed and\/or available to evaluate the (intelligence or data) problem.
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    • Collaborate with data collectors and analysts to identify and close gaps on complex monitoring problems.
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    • Provide accurate, timely, complex, and sophisticated data analysis.
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      Key Required Skills:<\/b><\/span><\/span><\/u>
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      • Solid Experience with Natural Language Processing (NLP), Python, NLP frameworks, SQL, Pandas, NLTK and SPACy.
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      • Experience with Generative AI and Large Language Models (LLM)
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      • Excellent Communication skills.
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        Requirements<\/h3>\n
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        Skills Requirements:<\/b><\/span><\/span><\/span>
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        Basic Qualification:<\/b><\/span><\/span><\/span><\/u>
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        • Master's and 10+ years of experience, Bachelor's and 12+ years of experience or 18+ years in lieu of a degree<\/span><\/span><\/span>
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        • Bachelor's degree in Statistics, Applied Mathematics, Computer Science, or Information Science with industry experience on Python, NLP frameworks, SQL, Pandas, NLTK and SPACy, data science, and AI\/ML\/LLM engineering.<\/span><\/span><\/span>
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        • Overall 10+ years' experience in IT industry<\/span><\/span><\/span>
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          Required Skills:<\/b><\/span><\/span><\/span><\/u>
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          • Solid Experience with Natural Language Processing (NLP), Python, NLP frameworks, SQL, Pandas, NLTK and SPACy.<\/span><\/span><\/span>
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          • Experience with Generative AI and Large Language Models (LLM)<\/span><\/span><\/span>
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          • Evidence of true self\-starter and operating independently.<\/span><\/span><\/span>
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          • Fluency in Python Programming, version control and collaboration with GIT, standard Python packages (ex. Pandas, numpy, matplotlib) and ML frameworks<\/span><\/span><\/span>
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          • Knowledge of TensorFlow, PyTorch, Pandas, scikit\-learn, NLTK, Azure ML (optional), Amazon Web Services EC2.<\/span><\/span><\/span>
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          • Experience with scalable data engineering frameworks such as Apache Spark and orchestration frameworks such as Airflow, and\/or experience with semantic search.<\/span><\/span><\/span>
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          • Expert knowledge in conducting data analysis and applying advanced statistical concepts and ML methods to build, train, test, and evaluate a variety of supervised and unsupervised analytic models.<\/span><\/span><\/span>
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          • Experience with ML model deployment and operations like DevOps, MLOps, LLMOps.<\/span><\/span><\/span>
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          • Experience with NLP and Generative AI libraries like regular expressions (e.g., spacy, langchain), text annotation tools and semantic frameworks.<\/span><\/span><\/span>
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          • Ability to clean and process large amounts of real\-world data.<\/span><\/span><\/span>
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          • Experience retrieving and manipulating data from a variety of data sources included DB2, Oracle, SQL Server, Hadoop and flat files.<\/span><\/span><\/span>
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          • Excellent Communication skills.<\/span><\/span><\/span>
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          • Experience with database management systems (e.g., PostgresSQL, MySQL, SQLite, SQL, etc.)<\/span><\/span><\/span>
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          • Excellent analytical skills to identify potential risks and propose effective solutions.<\/span><\/span><\/span>
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          • Excellent problem\-solving skills, ability to collaborate with cross\-functional teams and proven communication in written and verbal formats to various audiences to include executive leadership.<\/span><\/span><\/span>
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            Desired Skills:<\/b><\/span><\/span><\/span><\/u>
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            • Prior experience with federal or state governments IT projects.<\/span><\/span><\/span>
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            • Industry experience preferred<\/span><\/span><\/span>
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            • Experience with, or the ability and willingness to learn distributed processing via the Hadoop ecosystem, i.e., Spark, Impala and Hive.<\/span><\/span><\/span>
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            • Experience working in an analytical research environment.<\/span><\/span><\/span>
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            • Experience in parallel processing such as GPU programming with CUDA<\/span><\/span><\/span>
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            • Experience with Mathematica<\/span><\/span><\/span>
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            • Experience using markup languages such as LaTeX, HTML, etc.<\/span><\/span><\/span>
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            • Experience with Natural Language Processing for anomaly detection<\/span><\/span><\/span>.
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