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Data Annotation Engineer Jobs in Washington, DC (NOW HIRING)

YO AI Labs

AI Consulting Expert - Remote

Washington, DC · Remote

$100 - $200/hr

Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical & Report Writing * Business Communication * Content Review & Editing * Data Interpretation * Data Annotation * Fact Checking

New

Beyond SOF

DATA ENGINEER

Reston, VA · On-site

$119K - $143K/yr

Java -JDK 1.6+, Model View Controller (MVC) architecture, Annotation, Servelet 2.5/Java Server ... SSL programming and configuration, CAPCO (rules and automated parsing or validation). Access ...

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Showing results 21-40

All JobsData Annotation Engineer JobsData Annotation Engineer Jobs in Washington, DC

Data Annotation Engineer information

See Washington, DC salary details

$58.3K

$167K

$223.1K

How much do data annotation engineer jobs pay per year?

As of Aug 14, 2026, the average yearly pay for data annotation engineer in Washington, DC is $167,014.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,100.00 and $222,000.00 per year, depending on experience, location, and employer.

What are the main challenges faced by data annotation engineers in their daily work?

One of the main challenges Data Annotation Engineers face is ensuring consistent accuracy and quality in labeling large and often complex datasets. Attention to detail is critical, as even small errors can significantly affect machine learning model performance. Additionally, engineers must frequently adapt to evolving annotation guidelines and emerging data types, which requires ongoing learning and flexibility. Collaboration with data scientists and project managers is common to clarify requirements and resolve ambiguities, making strong communication skills essential for success.

What are the key skills and qualifications needed to thrive as a data annotation engineer?

To thrive as a Data Annotation Engineer, you need a strong background in data analysis, attention to detail, and familiarity with annotation processes, often supported by a degree in computer science or a related field. Proficiency with annotation tools like Labelbox, CVAT, or VIA, and understanding of data formats used in machine learning, is commonly required. Excellent communication, collaboration, and organizational skills help you effectively manage projects and cooperate with cross-functional teams. These abilities are crucial for delivering high-quality labeled data, which directly impacts the performance of AI and machine learning models.

What is a data annotation engineer?

A Data Annotation Engineer is responsible for labeling and annotating data—such as text, images, audio, or video—to train machine learning models. They ensure that data is accurately categorized and structured to improve model performance. This role often involves using specialized annotation tools, following detailed guidelines, and working closely with data scientists and AI teams. Data Annotation Engineers play a crucial role in the development of AI applications by providing high-quality labeled datasets for supervised learning.

What are popular job titles related to Data Annotation Engineer jobs in Washington, DC?

For Data Annotation Engineer jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Data Annotation Engineer jobs in Washington, DC look for?

The top searched job categories for Data Annotation Engineer jobs in Washington, DC are:

Data Annotation Engineer jobs near you
Infographic showing various Data Annotation Engineer job openings in Washington, DC as of August 2026, with employment types broken down into 53% Full Time, and 47% Contract. Highlights an 77% In-person, and 23% Remote job distribution, with an average salary of $167,014 per year, or $80.3 per hour.

Machine Learning Engineer - Computer Vision

CaseGuard

Arlington, VA • On-site

Full-time

Re-posted 4 days ago

Job description

Job Summary:
CaseGuard is seeking a highly skilled and motivated Machine Learning Engineer specializing in Computer Vision to join their team. The role involves developing and deploying machine learning models focused on image and video processing, collaborating with cross-functional teams to design and optimize vision-based AI solutions.
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 a management solutions company. Founded in , the company is headquartered in Sterling, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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