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Freelance Machine Learning Data Annotation Jobs in Virginia

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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 · On-site

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

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.
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What job categories do people searching Freelance Machine Learning Data Annotation jobs in Virginia look for? The top searched job categories for Freelance Machine Learning Data Annotation jobs in Virginia are:
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Freelance Machine Learning Data Annotation jobs near you
Machine Learning Engineer - Computer Vision

Machine Learning Engineer - Computer Vision

CaseGuard

Arlington, VA • On-site

Full-time

Posted 28 days ago

Job description

Job Summary:
CaseGuard is a software company that helps law enforcement agencies, federal agencies, hospitals, schools, airports, and others manage all their media redaction needs in one easy-to-use redaction software. They are seeking a highly skilled and motivated Machine Learning Engineer specializing in Computer Vision to develop and deploy machine learning models focused on image and video processing.
Responsibilities:
• Design, develop, and deploy computer vision models for tasks such as object detection, object tracking, video segmentation, and facial recognition.
• Optimize and fine-tune deep learning algorithms for real-time performance.
• Work closely with the software engineers and product teams to identify opportunities for leveraging data.
• Collect, clean, and preprocess large datasets to prepare for model training and evaluation.
• Evaluate and optimize machine learning models for accuracy, performance, and scalability.
• Deploy models into production environments and monitor their performance to ensure reliability.
• Stay up-to-date with the latest advancements in computer vision and artificial intelligence.
• Collaborate with cross-functional teams to integrate machine learning solutions into business processes.
• Document processes, models, and implementations to ensure reproducibility and scalability.
Qualifications:
Required:
• Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Experience in deep learning models, their training, and hyperparameter tuning using libraries such as TensorFlow, PyTorch, and Transformers or other Huggingface tools.
• Experience with data manipulation tools such as Pandas, NumPy, and SQL.
• Strong programming skills in Python and C++.
• Experience in MLOps principles and model deployment and instrumentation on cloud platforms such as AWS, Azure, or Google Cloud for model deployment and knowledge with efficient serving tools such as ONNX, triton, and vllm.
• Proficiency in working with image and video data, including preprocessing and augmentation techniques.
• Strong understanding of machine learning algorithms, including supervised and unsupervised learning and deep learning.
• Strong communication skills and the ability to work collaboratively in a team environment.
Preferred:
• Familiarity with containerization and orchestration tools like Docker and Kubernetes.
• Experience with version control systems such as Git.
• Understanding software engineering best practices, including code review, testing, and documentation.
• Experience with Large Language Models (LLMs) is a great plus.
• Experience with data annotation tools and processes.
Company:
CaseGuard is the world’s leading AI-powered Redaction and Investigation Solution. Founded in , the company is headquartered in Arlington, Virginia, US, , with a team of 51-200 employees. The company is currently Growth Stage.

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