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Freelance Machine Learning Data Annotation Jobs in Silver Spring, MD

Aitopics

Featured Feat. Data Scientist

Washington, DC · On-site

$80 - $157/hr

Monitor AI machine learning biotechnology and national security policy trends Skills * A/B | A/B ... Flexible schedule | Freelance opportunities | Part-time hours | Project based work * Part-time ...

Unissant

Machine Learning Engineer

Ashburn, VA · On-site

$110 - $170/hr

We apply our domain expertise, data acumen, and technology know-how to achieve breakthrough results ... We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA.

UNISSANT

Machine Learning Engineer

Ashburn, VA · On-site

We apply our domain expertise, data acumen, and technology know-how to achieve breakthrough results ... We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA.

Unissant

Machine Learning Engineer

Ashburn, VA · On-site

$112K - $177K/yr

We apply our domain expertise, data acumen, and technology know-how to achieve breakthrough results ... We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA.

Comcast

Engineer 6, Machine Learning, Data & AI

Reston, VA · On-site +1

$119K - $143K/yr

Experience supporting AI, machine learning, advanced analytics, or data modernization initiatives. * Demonstrated success influencing outcomes across large, matrixed organizations. Technical ...

Seekr

Senior Data Scientist

Reston, VA · On-site

Manage machine learning algorithm lifecycle * Support pre-sales efforts, identifying how the Seekr Platform could help satisfy customer requirements * Coordinate data collection and annotation ...

Seekr

Senior Data Scientist

Reston, VA · On-site

Manage machine learning algorithm lifecycle * Support pre-sales efforts, identifying how the Seekr Platform could help satisfy customer requirements * Coordinate data collection and annotation ...

Seekr

Senior Data Scientist

Reston, VA · On-site

Manage machine learning algorithm lifecycle * Support pre-sales efforts, identifying how the Seekr Platform could help satisfy customer requirements * Coordinate data collection and annotation ...

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All JobsMachine Learning Data Annotation JobsFreelance Machine Learning Data Annotation JobsFreelance Machine Learning Data Annotation Jobs in Silver Spring, MD

Freelance Machine Learning Data Annotation information

See Silver Spring, MD salary details

$13

$22

$36

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 Silver Spring, MD is $22.61, according to ZipRecruiter salary data. Most workers in this role earn between $17.88 and $25.87 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 are popular job titles related to Freelance Machine Learning Data Annotation jobs in Silver Spring, MD?

For Freelance Machine Learning Data Annotation jobs in Silver Spring, MD, the most frequently searched job titles are:

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

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

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

Freelance Machine Learning Data Annotation jobs near you
Infographic showing various Freelance Machine Learning Data Annotation job openings in Silver Spring, MD as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $47,019 per year, or $22.6 per hour.

Machine Learning Engineer with Security Clearance

AtOrchard LLC

Silver Spring, MD • On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago

Job description

Machine Learning EngineerRemote with occasional travel to Silver Spring, MD About @Orchard: @Orchard is a growing Woman-Owned Small Business and federal prime contractor delivering mission-critical science, data, technology, program management, and workforce solutions. Since 2010, we have built high-performing teams and disciplined delivery systems that help federal agencies launch complex programs, sustain performance, and achieve meaningful mission outcomes. Position Summary: @Orchard LLC is seeking an Machine Learning Engineer to support the National Oceanic and Atmospheric Administration (NOAA), Office of Ocean Exploration. The Machine Learning Engineer will develop and apply machine learning capabilities to help NOAA Ocean Exploration analyze the large volumes of scientific data and video generated during ocean exploration expeditions. Working at the intersection of computer science, marine science, and data analytics, this position will develop software, algorithms, and analytical workflows that help identify scientifically significant characteristics, fauna, shapes, movement, and other features within complex scientific datasets and video streams. The successful candidate will collaborate with marine scientists, engineers, data specialists, and other technical professionals to improve the efficiency and consistency of scientific data analysis. The role will help reduce manual review time, support annotation and characterization of observations, and create repeatable tools that enable scientists to extract meaningful information from increasingly large ocean exploration datasets. This position is contingent upon contract award. Mission Impact: This position applies emerging AI and machine learning technologies to one of the world's most challenging data environments-ocean exploration. Your work will help NOAA scientists analyze massive volumes of expedition data and video more efficiently, accelerating the identification and characterization of marine life and other scientifically significant observations. Key Responsibilities: AI & Machine Learning Development * Develop machine learning capabilities for evaluating large volumes of ocean exploration data and streaming video.
* Design, develop, test, and refine algorithms and software that identify specific characteristics, shapes, movement, fauna, and other features within scientific data and video. 
* Develop computer-language subroutines, scripts, and programs that support automated or semi-automated data analysis, annotation, and characterization. 
* Apply appropriate machine learning and computer vision techniques to improve the efficiency and consistency of scientific data review. 
* Evaluate model performance and refine approaches based on scientific objectives and observed results.  Scientific Data & Video Analysis * Work with large scientific datasets and high-volume expedition video to identify patterns and features relevant to ocean exploration. 
* Collaborate with marine scientists to translate scientific questions and observation requirements into computational approaches.
* Support development of tools that enable scientists to efficiently locate, annotate, classify, and characterize observations.
* Assist in developing repeatable analytical workflows that can be applied to future expeditions and datasets. 
* Support integration of AI/ML outputs into broader scientific data analysis, annotation, and ocean exploration workflows. Software Development & Documentation * Develop maintainable and reusable code supporting machine learning and data-analysis capabilities.
* Document software development, algorithms, workflows, model changes, and system updates to support future corrections and enhancements. 
* Test and troubleshoot applications and analytical workflows to ensure reliable performance.
* Recommend improvements to software, analytical methods, and machine learning workflows.
* Support software corrections and updates as required.  Scientific Collaboration * Collaborate with marine scientists, GIS specialists, web developers, engineers, and other technical professionals. 
* Participate in technical discussions, scientific meetings, and project planning activities. 
* Translate technical machine learning concepts into understandable information for scientific and program stakeholders. 
* Support technical reports, presentations, demonstrations, and other program deliverables.  Operational Support * Support response to urgent software or analytical issues affecting supported capabilities, including occasional work outside normal business hours when required
* Support troubleshooting and resolution of issues affecting machine learning applications and associated web or data capabilities. Requirements * Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Marine Science, Oceanography, or related discipline. Master's degree preferred.
* Experience developing or applying machine learning solutions for data analysis, computer vision, video analysis, or related applications.
* Programming experience in Python or another modern programming language.
* Experience working with large datasets and developing repeatable data-analysis workflows.
* Understanding of machine learning concepts, model development, evaluation, and optimization.
* Strong analytical and problem-solving skills.
* Ability to collaborate effectively with scientists and technical professionals from different disciplines.
* Excellent written and verbal communication skills.
* Proficiency with Microsoft Office 365, Google Workspace, and Adobe Acrobat.
* Occasional domestic travel may be required to support scientific meetings, workshops, planning sessions, training activities, or other program requirements consistent with contract needs.
*  Must be eligible to obtain and maintain a Department of Commerce / NOAA federal background investigation and suitability determination and be authorized to work in the United States without employer sponsorship. 
Preferred Skills and Experience: * Experience applying AI or machine learning to scientific, environmental, marine, or oceanographic datasets is preferred.
* Experience with computer vision, image recognition, object detection, video analytics, or image classification.
* Experience working with high-volume video or streaming data.
* Experience with deep learning frameworks such as PyTorch or TensorFlow.
* Experience with scientific Python libraries and data-analysis tools.
* Experience supporting NOAA, other federal agencies, academic research organizations, or marine science programs.
* Familiarity with marine organisms, oceanographic data, or scientific expedition environments. Technical Skills: * Python 
* Data Analysis 
* Large-Scale Data Processing 
* Algorithm Development 
* Software Testing & Troubleshooting 
* Scientific Data Workflows  Compensation: The anticipated salary range for this position depends on the candidate's qualifications, relevant scientific experience, education, and overall experience supporting similar federal programs. What We Offer: Competitive base salary with opportunities for advancement, career growth and professional development, work-life balance, comprehensive benefits including health, dental, vision, life insurance, 401(k), generous PTO, and paid federal holidays. If you are passionate about artificial intelligence, machine learning, and applying innovative technology to ocean exploration, we encourage you to join our team and help transform massive volumes of scientific data into discoveries that advance our understanding of the world's oceans. @Orchard is an equal opportunity employer. We encourage all qualified candidates to apply, regardless of race, gender, age, disability, or other protected characteristics. To learn more about our other exciting opportunities, visit our Jobs Page at www.atorchard.com.

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