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Freelance Machine Learning Data Annotation Jobs in Clinton, MD

GRVTY

Data Scientist 2

Annapolis Junction, MD · On-site

We have varying levels of Data Scientist roles, depending on years of experience and education ... This role combines artificial intelligence and machine learning skills with a strong foundation in ...

ProSidian Consulting

Machine Learning Engineer

Alexandria, VA · Hybrid

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

ProSidian.com ProSidian Seeks a Machine Learning Engineer | Data Management & Business Intelligence - Data Scientist Support [NSF0112112] for Program Support on a Exempt W2: No Overtime Pay Basis ...

ProSidian Consulting

Machine Learning Engineer

Alexandria, VA · Hybrid

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

We seek Machine Learning Engineer | Data Management & Business Intelligence - Predictive Workforce Analytics [NSF0117117] candidates with relevant Government And Public Services Sector Experience ...

Jobtailor

Data Scientist

Washington, DC · On-site

$110 - $170/hr

Select statistical and machine learning methods appropriate to the question and evidence * Conduct exploratory data analysis covering distributions, relationships, outliers, missingness, and data ...

New

CoVar

Senior Machine Learning Engineer

Mclean, VA

$105K - $145K/yr

Senior Machine Learning Engineer Location: McLean, VA (hybrid); occasional travel to Durham, NC and ... Experience with data curation/annotation workflows and dataset quality control. * Software ...

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Freelance Machine Learning Data Annotation information

See Clinton, MD salary details

$12

$21

$34

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

As of Aug 16, 2026, the average hourly pay for freelance machine learning data annotation in Clinton, MD is $21.74, according to ZipRecruiter salary data. Most workers in this role earn between $17.21 and $24.86 per hour, depending on experience, location, and employer.

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.

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 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 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 job categories do people searching Freelance Machine Learning Data Annotation jobs in Clinton, MD look for?

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

What cities near Clinton, MD are hiring for Freelance Machine Learning Data Annotation jobs?

Cities near Clinton, MD with the most Freelance Machine Learning Data Annotation job openings:

Freelance Machine Learning Data Annotation jobs near you

AI/ML Test Engineer

Modern Technology Solutions, Inc. (MTSI)

Springfield, VA • On-site

Full-time

Posted 11 days ago

Job description

Job Summary:
Modern Technology Solutions, Inc. (MTSI) is hiring an AI/ML Test Engineer in Springfield, VA. The role involves executing system-level AI/Machine Learning evaluation activities, performing integration testing, and supporting automated evaluation pipelines for AI/ML model testing and performance assessment.
Responsibilities:
• Execute system-level AI/Machine Learning evaluation activities within the Test & Evaluation (T&E) environment supporting mission-focused operational testing.
• Perform integration testing, data capture, drift detection, and operational validation activities across AI/ML evaluation workflows.
• Support automated and semi-automated evaluation pipelines for AI/ML model testing and performance assessment.
• Develop, maintain, and refine data annotation workflows supporting operational evaluation requirements.
• Validate operational datasets and support testing activities across multiple models, datasets, and mission scenarios.
• Conduct integration testing of AI/ML models within operationally representative environments and workflows.
• Adapt evaluation procedures and workflows to address evolving GEOINT data conditions and operational mission requirements.
• Support high-throughput and parallel model evaluation activities to maintain alignment with mission timelines and operational priorities.
• Identify and mitigate data drift, performance degradation, and workflow issues impacting evaluation reliability.
• Collaborate with Senior AI/ML Test Engineers, data scientists, software engineers, and mission stakeholders to support scalable T&E execution.
• Contribute to technical documentation, evaluation reporting, and customer briefings supporting operational decision-making.
Qualifications:
Required:
• U.S. citizenship
• TS/SCI clearance
• CI Polygraph
• 4+ years of experience supporting AI/ML testing, system integration, operational testing, or evaluation workflows.
• Familiarity with automated testing pipelines, operational data validation, and model performance assessment concepts.
• Ability to support multiple evaluation activities across dynamic operational environments.
• Experience troubleshooting technical workflow or data-related issues in support of operational objectives.
• Strong analytical, organizational, and communication skills.
• Bachelor’s degree in IT or STEM related field, or additional relevant experience in lieu of a degree.
• Active TS/SCI clearance and the ability to pass a CI polygraph within 30 days.
Preferred:
• Experience supporting DoD, NGA, or Intelligence Community programs.
• Familiarity with AI/ML model evaluation, GEOINT workflows, and operational testing environments.
• Experience working in Agile, DevSecOps, or cloud-based operational environments.
• Familiarity with annotation workflows, data capture pipelines, drift detection, and automated evaluation tools.
• Experience supporting scalable AI/ML evaluation or mission-focused T&E activities.
Company:
Modern Technology Solutions, Inc. Founded in 1993, the company is headquartered in Alexandria, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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