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Freelance Machine Learning Data Annotation Jobs in Virginia

USM

JB061715 - Data Scientist

Mclean, VA · On-site

... Develop machine learning algorithm Identify trends and business insights from data Create ... dashboards and visualization Work with stakeholders to solve business problem Present findings and ...

USM

JB061715 - Data Scientist

Mclean, VA · On-site

... Develop machine learning algorithm Identify trends and business insights from data Create ... dashboards and visualization Work with stakeholders to solve business problem Present findings and ...

USM

JB061715 - Data Scientist

Mclean, VA · On-site

... Develop machine learning algorithm Identify trends and business insights from data Create ... dashboards and visualization Work with stakeholders to solve business problem Present findings and ...

USM

JB061715 - Data Scientist

Mclean, VA · On-site

... Develop machine learning algorithm Identify trends and business insights from data Create ... dashboards and visualization Work with stakeholders to solve business problem Present findings and ...

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 ...

Cymertek

Machine Learning Engineer

Tysons, VA · On-site

Machine Learning Engineer LOCATION Tysons, VA 22182 CLEARANCE TS/SCI Full Poly (Please note this ... You will collaborate with data scientists, engineers, and product teams to turn data into ...

Cymertek

Machine Learning Engineer

Reston, VA · On-site

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this ... You will collaborate with data scientists, engineers, and product teams to turn data into ...

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Freelance Machine Learning Data Annotation information

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 the most commonly searched types of Machine Learning Data Annotation jobs in Virginia? The most popular types of Machine Learning Data Annotation jobs in Virginia are:
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Freelance Machine Learning Data Annotation jobs near you
Machine Learning Engineer in Reston VA

Machine Learning Engineer in Reston VA

Hexaware Technologies, Inc

Reston, VA • On-site

Other

Posted 8 days ago

Job description

AI/ML Engineer LLM & AWS Integration

Reston VA

  • 3+ years of experience in machine learning, data science, or AI engineering.
  • Hands-on experience with LLMs (e.g., OpenAI, Anthropic, Cohere) and prompt engineering.
  • Strong proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • Deep experience with AWS services, especially Bedrock, S3, EC2, and Lambda
  • Familiarity with MLOps practices and tools for model deployment and monitoring.
  • Excellent problem-solving skills and ability to communicate technical concepts to non-technical stakeholders.
  • Strong programming skills in data analytics related languages and libraries, such as Python, R, Pandas, or JavaScript.
  • Experience with AWS SageMaker for model development and model deployment.
  • Understanding of quantitative/statistical/ML/AI modeling methodologies.
  • Experience in ML engineering, including hands-on experience with Generative AI/LLMs.
  • Experience with developing and deploying AI Agents for business problems.

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