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Prompt Data Annotation Ai Jobs in Virginia (NOW HIRING)

Steampunk

Prompt Engineer

Mclean, VA · On-site

$115K - $140K/yr

Overview We are seeking a Prompt Engineer design, test, and refine interaction patterns for ... You will contribute to the growth of our AI & Data Exploitation Practice! Qualifications * Ability ...

AIToolboard

AI and ML Data Scientist

Mclean, VA · On-site

$120 - $160/hr

You'll design and implement AI agents, retrieval-augmented generation pipelines, evaluation frameworks, prompt strategies, data processing workflows, and mission-focused prototypes. You'll help ...

Steampunk

Prompt Engineer

Mclean, VA

$115K - $140K/yr

Overview We are seeking a Prompt Engineer design, test, and refine interaction patterns for ... You will contribute to the growth of our AI & Data Exploitation Practice! Qualifications * Ability ...

Seekr

Senior Data Scientist

Reston, VA · On-site

Coordinate data collection and annotation efforts for supervised training efforts * Design and ... Familiar with generative AI concepts like RAG, prompt engineering, agents, structured output, multi ...

Nestle

Expert Data Scientist (AI)

Arlington, VA

Position Summary Join Nestle IT & Digital as an Expert AI Data Scientist supporting Nestle USA ... Experience directing AI agents or agentic workflows to do substantive work, not just single-prompt ...

Unissant

AI Data Scientist

Ashburn, VA · On-site

They are seeking an AI Data Scientist to support federal customer initiatives by designing machine ... Prompt and Context engineering. • Experience with advanced techniques like deep learning ...

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All JobsPrompt Data Annotation Ai JobsPrompt Data Annotation Ai Jobs in Virginia

Prompt Data Annotation Ai information

What is the difference between Prompt Data Annotation Ai vs Data Labeler?

AspectPrompt Data Annotation AiData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, often with AI teamsRemote or on-site, often with data teams
Industry UsageAI development, machine learning projectsData management, machine learning datasets
Job FocusAnnotating data for AI prompts and modelsLabeling data for training AI algorithms

Prompt Data Annotation Ai specialists focus on creating high-quality annotations specifically for AI prompts, ensuring models understand context. Data Labelers perform similar tasks but may work on broader datasets. Both roles require attention to detail and are vital in AI development, often overlapping but with different emphasis on prompt-specific annotation versus general data labeling.

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Infographic showing various Prompt Data Annotation Ai job openings in Virginia as of June 2026, with employment types broken down into 70% Full Time, 28% Part Time, 1% Contract, and 1% Nights. Highlights an 74% Physical, 3% Hybrid, and 23% Remote job distribution.

Machine Learning Engineer - Computer Vision

CaseGuard

Arlington, VA • On-site

Full-time

Re-posted 29 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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