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Freelance Machine Learning Data Annotation Jobs in Silver Spring, MD

MANTECH

Data Scientist

Fort George G Meade, MD

We are seeking talented and motivated Data Scientists with expertise in machine learning, statistical analysis, and artificial intelligence to join our team. In these roles, you will be responsible ...

MANTECH

Data Scientist

Fort George G Meade, MD · On-site

We are seeking talented and motivated Data Scientists with expertise in machine learning, statistical analysis, and artificial intelligence to join our team. In these roles, you will be responsible ...

MANTECH

Data Scientist

Fort George G Meade, MD · On-site

We are seeking talented and motivated Data Scientists with expertise in machine learning, statistical analysis, and artificial intelligence to join our team. In these roles, you will be responsible ...

CoVar

Machine Learning Engineer

Mclean, VA · On-site

$83K - $111K/yr

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

Unissant

Data Scientist

Ashburn, VA · On-site

$99K - $164K/yr

Familiarity with supervised and unsupervised machine-learning techniques and methods. * Experience performing data mining, data analysis, image-data preparation, labeling or annotation, and training ...

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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 Sep 8, 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:

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

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 September 2026, with employment types broken down into 1% Internship, 1% As Needed, 83% Full Time, 11% Part Time, 2% Temporary, and 2% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution, with an average salary of $47,019 per year, or $22.6 per hour.

Data Scientist / Machine Learning (TS SCI + Poly is Required)

Fort George G Meade, MD • On-site

Aperio Global
Guided Missile and Space Vehicle Manufacturing • 1 - 10 employees
Learn more about Aperio Globalexternal

Full-time

Posted 21 days ago

Job description

Aperio Global is seeking a Data Scientist to develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets; prototype or consider several algorithms and decide upon final model based on suitable performance metrics; build models or develop experiments to generate data when training or example datasets are unavailable; generate reports and visualizations that summarize datasets and provide data-driven insights to customers; partner with subject matter experts to translate manual data analysis into automated analytics; implement prototype algorithms within production frameworks for integration into analyst workflows.

Overview: 

Level 1

Produce data visualizations that provide insight into dataset structure and meaning.
Collaborate with subject matters experts (SMEs) to identify important information in raw data
and develop scripts that extract this information from a variety of data formats (e.g., SQL tables,
structured metadata, network logs).
Incorporate SME input into feature vectors suitable for analytic development and testing.
Translate customer qualitative analysis process and goals into quantitative formulations that are coded into software prototypes.
Develop and implement statistical, machine learning, and heuristic techniques to create descriptive, predictive, and prescriptive analytics.
Develop statistical tests to make data-driven recommendations and decisions

Level 2

Develop experiments to collect data or models to simulate data when required data are unavailable.
Develop feature vectors for input into machine learning algorithms.
Identify the most appropriate algorithm for a given dataset and tune input and model parameters.
Evaluate and validate the performance of analytics using standard techniques and metrics (e.g. cross validation, ROC curves, confusion matrices).
Evaluate individual analytic efforts and make recommendations in the analytic development process.
Recommend solutions that can scale to large datasets.
Collaborate with software engineers, cloud developers, and appropriate stakeholders to develop production analytics.
Develop and train machine learning systems based on statistical analysis of data characteristics to support mission automation
Security Clearance Requirements:

This position requires all candidates to be U.S. Citizens and possess an active TS/SCI Security Clearance with a Polygraph.

Qualifications:

Requires a Bachelor's degree in a relevant discipline (e.g., statistics, mathematics, operations research, and engineering or computer science) from an accredited college or university, and four (4) years of experience analyzing datasets and developing analytics and two (2) year of experience programming with data analysis software such as R, Python, SAS, or MATLAB.
A Master's degree in relevant discipline may be substituted for two (2) years of relevant experience analyzing datasets and developing analytics, and one (1) year of relevant experience programming with data analysis software such as R, Python, SAS, or MATLAB.
In lieu of a Bachelor's Degree, an additional four (4) years of relevant experience may be substituted for a total of eight (8) years of relevant experience analyzing datasets and developing analytics, and two (2) years of experience programming with data analysis software such as R, Python, SAS, or MATLAB.

Level 2: 
A PhD in relevant discipline may be substituted for four (4) years relevant experience reducing the requirement to four (4) years of relevant experience analyzing datasets and developing analytics, and one (1) year of experience programming with data analysis software such as R, Python, SAS, or MATLAB.

Anticipated Salary Range; 
LEVEL 1     150-170  
LEVEL 2    170-190

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