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Amazon Data Annotation Jobs in Maryland (NOW HIRING)

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Amazon Data Annotation information

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$9

$24

$44

How much do amazon data annotation jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for amazon data annotation in Maryland is $24.02, according to ZipRecruiter salary data. Most workers in this role earn between $16.77 and $29.71 per hour, depending on experience, location, and employer.

What is an Amazon Data Annotation?

An Amazon Data Annotation job involves labeling or tagging data such as text, images, audio, or videos to improve machine learning models. Annotators follow specific guidelines to provide accurate labels that help refine Amazon's AI systems, including Alexa and product recommendations. This work is often detail-oriented and may require understanding context, language nuances, or specific industry knowledge. The role can be full-time or contract-based and may involve remote or on-site work, depending on the project.

What does an Amazon Data Annotation do?

A typical day as an Amazon Data Annotation specialist involves reviewing, labeling, and annotating diverse datasets, such as images, videos, or text, using specialized software and following detailed guidelines. You may collaborate with team members or project leads to clarify instructions and ensure consistency across annotations. Periodic quality checks and feedback sessions are common, helping you refine your work and maintain high standards. While much of the work is independent, clear communication and responsiveness are important for meeting project deadlines and successfully supporting Amazon’s AI development goals.

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

To thrive as an Amazon Data Annotation specialist, you need keen attention to detail, accuracy, and proficiency in data labeling or annotation, often supported by a background in data entry or related fields. Familiarity with annotation tools, Amazon’s proprietary data platforms, and in some cases basic understanding of programming languages or machine learning concepts is beneficial. Strong communication skills, adaptability, and the ability to work independently or with minimal supervision help individuals excel in the role. These abilities are crucial for ensuring high-quality, reliable data that supports Amazon’s AI and machine learning initiatives.

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 Amazon Data Annotation jobs in Maryland?

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

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

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

Amazon Data Annotation jobs near you
Infographic showing various Amazon Data Annotation job openings in Maryland as of August 2026, with employment types broken down into 96% Full Time, and 4% Contract. Highlights an 84% In-person, and 16% Remote job distribution, with an average salary of $49,955 per year, or $24 per hour.

Senior Data Scientist

Ellicott City, MD • On-site

Omm IT Solutions
See more jobs at Omm IT Solutionsexternal

Contractor

Re-posted 18 days ago

Job description

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PLEASE NOTE:<\/b><\/span><\/span><\/u>\n
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  • It is 100% onsite position in Woodlawn, MD.<\/b>\n
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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>\n
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  • Candidate must be able to obtain and maintain a public trust clearance<\/b>\n
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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>\n
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    Position Description:<\/b><\/span><\/span><\/u>\n
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    • Hands on experience in Python, NLP frameworks, SQL, Pandas, NLTK, SPACy and LLMs\n
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    • Well versed in SQL and analyzing trends and transactional data.\n
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    • Understand real world challenges and develop automated data solutions\n
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    • Develop, test, and deploy new techniques for NLP understanding\n
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    • Scalable development\/deployment of ML and Generative AI approaches (such as Large Language Models (LLMs)\n
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    • Train and optimize NLP\/LLM models and create Python based pipelines\n
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    • Experience building cloud native solutions on AWS\n
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    • Determine the nature of analytic problems, evaluate options, and offer recommendations for resolution.\n
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    • Advise on the methods and data needed and\/or available to evaluate the (intelligence or data) problem.\n
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    • Collaborate with data collectors and analysts to identify and close gaps on complex monitoring problems.\n
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    • Provide accurate, timely, complex, and sophisticated data analysis.\n
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      Key Required Skills:<\/b><\/span><\/span><\/u>\n
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      • Solid Experience with Natural Language Processing (NLP), Python, NLP frameworks, SQL, Pandas, NLTK and SPACy.\n
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      • Experience with Generative AI and Large Language Models (LLM)\n
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      • Excellent Communication skills.\n
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        \n \n Requirements<\/h3>\n
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        Skills Requirements:<\/b><\/span><\/span><\/span>\n
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        Basic Qualification:<\/b><\/span><\/span><\/span><\/u>\n
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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>\n
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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>\n
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        • Overall 10+ years' experience in IT industry<\/span><\/span><\/span>\n
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          Required Skills:<\/b><\/span><\/span><\/span><\/u>\n
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            \n
          • Solid Experience with Natural Language Processing (NLP), Python, NLP frameworks, SQL, Pandas, NLTK and SPACy.<\/span><\/span><\/span>\n
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          • Experience with Generative AI and Large Language Models (LLM)<\/span><\/span><\/span>\n
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          • Evidence of true self\-starter and operating independently.<\/span><\/span><\/span>\n
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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>\n
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          • Knowledge of TensorFlow, PyTorch, Pandas, scikit\-learn, NLTK, Azure ML (optional), Amazon Web Services EC2.<\/span><\/span><\/span>\n
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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>\n
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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>\n
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          • Experience with ML model deployment and operations like DevOps, MLOps, LLMOps.<\/span><\/span><\/span>\n
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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>\n
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          • Ability to clean and process large amounts of real\-world data.<\/span><\/span><\/span>\n
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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>\n
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          • Excellent Communication skills.<\/span><\/span><\/span>\n
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          • Experience with database management systems (e.g., PostgresSQL, MySQL, SQLite, SQL, etc.)<\/span><\/span><\/span>\n
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          • Excellent analytical skills to identify potential risks and propose effective solutions.<\/span><\/span><\/span>\n
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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>\n
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            Desired Skills:<\/b><\/span><\/span><\/span><\/u>\n
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            • Prior experience with federal or state governments IT projects.<\/span><\/span><\/span>\n
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            • Industry experience preferred<\/span><\/span><\/span>\n
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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>\n
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            • Experience working in an analytical research environment.<\/span><\/span><\/span>\n
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            • Experience in parallel processing such as GPU programming with CUDA<\/span><\/span><\/span>\n
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            • Experience with Mathematica<\/span><\/span><\/span>\n
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            • Experience using markup languages such as LaTeX, HTML, etc.<\/span><\/span><\/span>\n
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            • Experience with Natural Language Processing for anomaly detection<\/span><\/span><\/span>.\n
              <\/span><\/span><\/li>\n <\/ul>\n <\/div>\n <\/span>\n
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