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Freelance Machine Learning Data Annotation Jobs in Silver Spring, MD

Gormat

Data Scientist 3

Annapolis Junction, MD

... annotation of language data with parts of speech information, and improve existing models by ... Relevant experience must be in designing/implementing machine learning, data science, advanced ...

Gormat

Data Scientist 3

Annapolis Junction, MD · On-site

$132K - $147K/yr

... annotation of language data with parts of speech information, and improve existing models by ... Relevant experience must be in designing/implementing machine learning, data science, advanced ...

Gormat

Data Scientist 3

Annapolis Junction, MD · On-site

$132K - $147K/yr

... annotation of language data with parts of speech information, and improve existing models by ... Relevant experience must be in designing/implementing machine learning, data science, advanced ...

Full Scope

Machine Learning Engineer

Reston, VA

You will work closely with data scientists, engineers, and product managers to design, develop, and deploy machine learning models and solutions that drive business value. Key Responsibilities:

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 ...

1872 Consulting

Machine Learning Engineer

Reston, VA

You will be working closely with our Data Scientists, implementing highly available and scalable machine learning pipelines. If you are a Software Engineer passionate for technology who wants to work ...

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Freelance Machine Learning Data Annotation information

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$13

$22

$36

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

As of Jun 18, 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 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, and why are they important?

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 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
Machine Learning / Data Scientist

Machine Learning / Data Scientist

Parsons

Washington, DC

$88K - $154K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 days ago

Parsons rating

7.9

Company rating: 7.9 out of 10

Based on 44 frontline employees who took The Breakroom Quiz

156th of 355 rated engineering

Job description

In a world of possibilities, pursue one with endless opportunities. Imagine Next!At Parsons, you can imagine a career where you thrive, work with exceptional people, and be yourself. Guided by our leadership vision of valuing people, embracing agility, and fostering growth, we cultivate an innovative culture that empowers you to achieve your full potential. Unleash your talent and redefine what's possible.

Job Description:

We have a career opportunity for a Machine Learning / Data Scientist to develop advanced analytical models and experiments that enhance decision-making, improve forecasting, and uncover insights across mission and support activities. This role would be based in Washington, DC. Would be required to be on-site

This role will support the enablement of machine learning capabilities within our analytics environment, working closely with data analysts, engineers, and program stakeholders.

The Machine Learning / Data Scientist is a hands-on practitioner with strong capabilities in model development, data preparation, and analytical storytelling. This role requires the ability to frame complex problems, select appropriate modeling approaches, implement and validate models, and communicate results in accessible terms to non-technical audiences.

Key Responsibilities:

  • Design and implement machine learning and advanced analytics solutions that address operational, programmatic, or strategic questions.
  • Collaborate with stakeholders to define analytical problems, identify relevant data, and translate business needs into modeling requirements.
  • Prepare and engineer features from multiple data sources, ensuring data quality and suitability for modeling.
  • Develop, train, and validate models (e.g., classification, regression, clustering, forecasting) using appropriate techniques and tools.
  • Evaluate model performance, perform error analysis, and refine approaches to improve accuracy, robustness, and interpretability.
  • Integrate model outputs into dashboards, applications, or automated workflows, in coordination with analytics and development teams.
  • Document modeling approaches, assumptions, and results, and communicate findings through clear narratives and visualizations.
  • Support experimentation and pilot projects that explore new analytical techniques and tools.
  • Contribute to the development of standards and practices for responsible and sustainable use of advanced analytics.

Typical Assignments:

  • Building predictive or prescriptive models that support prioritization of projects, resource allocation, or risk assessment.
  • Conducting exploratory data analysis to identify patterns, anomalies, and opportunities for improved performance.
  • Developing prototypes of ML-enabled features that can be integrated into existing dashboards or applications.
  • Supporting performance management by providing advanced analyses of trends and drivers underlying key metrics.
  • Collaborating with data management staff to ensure datasets are suitable for modeling and reproducible analysis.
  • Preparing technical and non-technical presentations that summarize modeling methods, findings, and implications.

Education and Experience:

  • Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or a closely related field; a master's degree is preferred but not required, or equivalent work experience.
  • 5+ years of experience in data science, machine learning, or advanced analytics roles.
  • Demonstrated experience developing, validating, and deploying machine learning models using tools such as Python, R, or equivalent.
  • Strong background in statistics, model evaluation, and experimental design.
  • Experience with data preparation, feature engineering, and working with complex, multi-source datasets.
  • Familiarity with integrating model outputs into BI tools or applications (e.g., via APIs, embedded analytics) is preferred.
  • Experience working within mission-oriented or public sector environments (e.g., DHS, DoD) is a plus.

Security Clearance Requirement:

NoneThis position is part of our Critical Infrastructure team.For more than 80 years, our experts have designed and delivered the critical infrastructure that connects and protects communities around the world. We work in collaborative teams, both within the company and with our partners and customers, to plan, design, build, and modernize infrastructure. We take special pride in projects and solutions that improve communities as well as people's quality of life by promoting economic growth, enhancing mobility, and increasing sustainability and resiliency. Powered by our people, we provide the imagination necessary to support our customers' visions-and to help them see what's next!Salary Range: $88,400.00 - $154,700.00We value our employees and want our employees to take care of their overall wellbeing, which is why we offer best-in-class benefits such as medical, dental, vision, paid time off, Employee Stock Ownership Plan (ESOP), 401(k), life insurance, flexible work schedules, and holidays to fit your busy lifestyle!Parsons is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, veteran status or any other protected status.We truly invest and care about our employee's wellbeing and provide endless growth opportunities as the sky is the limit, so aim for the stars! Imagine next and join the Parsons quest-APPLY TODAY!

Parsons is aware of fraudulent recruitment practices. To learn more about recruitment fraud and how to report it, please refer tohttps://www.parsons.com/fraudulent-recruitment/.

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