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Data Labeling Jobs in Reston, VA (NOW HIRING)

AIToolboard

AI and ML Data Scientist

Mclean, VA · On-site

... labeling, classification models, model evaluation, and data quality assessment • Ability to translate military intelligence mission requirements into technical AI solutions, prototypes, and ...

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Data Labeling information

What is data labeling?

A Data Labeling job involves annotating or tagging data, such as images, text, audio, or videos, to help train machine learning models. Labelers follow specific guidelines to classify data accurately so that AI systems can learn patterns and make predictions. This role is essential in fields like computer vision, natural language processing, and speech recognition. Strong attention to detail and consistency are crucial for ensuring high-quality training datasets.

What are the typical day-to-day responsibilities of a data labeling professional?

A Data Labeling professional is primarily responsible for reviewing and accurately tagging images, text, audio, or video data according to specified guidelines. Daily tasks often include managing large datasets, using annotation software to classify data, and verifying the quality and accuracy of the labels. Collaboration with data scientists, project managers, and other annotators is common, especially when clarifying labeling guidelines or resolving ambiguities. Attention to detail is crucial, as high-quality labeled data directly impacts the effectiveness of machine learning models and AI applications. Most positions are structured in team environments, where productivity and communication skills help ensure project deadlines are met.

What are the key skills and qualifications needed to thrive in data labeling, and why are they important?

To thrive in Data Labeling, you need meticulous attention to detail, strong analytical abilities, and basic computer literacy, often supported by a high school diploma or equivalent. Familiarity with data annotation tools, image or text editing software, and experience with platforms like Labelbox or Amazon SageMaker Ground Truth are commonly advantageous. Exceptional concentration, patience, and the ability to follow precise instructions are valuable soft skills in this position. These skills and qualities are essential for ensuring the accuracy and consistency of labeled datasets, which are critical for training reliable AI and machine learning models.

How can I get started in data labeling?

To get started in data labeling, you should develop basic skills in data annotation tools and understand labeling guidelines for different data types such as images, text, or audio. Many entry-level positions require attention to detail and sometimes a background in relevant fields like computer science or linguistics; online courses and practice datasets can help build your skills. Additionally, creating a strong profile on job platforms and applying to companies that offer remote or flexible data labeling roles can increase your chances of starting in this field.

How much do data labelers make?

Data labelers typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the platform or employer. Some may work as freelancers or part-time, with pay rates varying accordingly.

Is data labeling a good career?

Data labeling is a growing field that involves annotating data for machine learning models, often requiring attention to detail and familiarity with tools like labeling platforms. It can offer flexible schedules and entry-level opportunities, but typically provides lower pay compared to other tech roles and may lack long-term career advancement without additional skills. Overall, it can be a suitable starting point for those interested in AI and data science, but may not be ideal as a long-term career without further development.

What are data labeling jobs?

Data labeling jobs involve annotating or tagging data such as images, text, or videos to help train machine learning models. These roles typically require attention to detail and familiarity with labeling tools or software, and may be performed remotely or in a team environment.

What are the most commonly searched types of Data Labeling jobs in Reston, VA?

The most popular types of Data Labeling jobs in Reston, VA are:

What are popular job titles related to Data Labeling jobs in Reston, VA?

For Data Labeling jobs in Reston, VA, the most frequently searched job titles are:

What job categories do people searching Data Labeling jobs in Reston, VA look for?

The top searched job categories for Data Labeling jobs in Reston, VA are:

What cities near Reston, VA are hiring for Data Labeling jobs?

Cities near Reston, VA with the most Data Labeling job openings:

Data Labeling jobs near you
Infographic showing various Data Labeling job openings in Reston, VA as of August 2026, with employment types broken down into 73% Full Time, 9% Part Time, 7% Temporary, and 11% Contract. Highlights an 85% In-person, and 15% Remote job distribution.

AI and ML Data Scientist

Mclean, VA • On-site

AIToolboard
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Re-posted 8 days ago

Job description

# AI and ML Data ScientistJobs via DiceMcLean, USPart-time## About the RoleJob Number: R0242343AI and ML Data ScientistThe Opportunity:As an Agentic AI Engineer and Data Scientist for military intelligence, you're excited by the opportunity to design, develop, and deploy advanced AI systems that help analysts transform complex, fragmented information into actionable intelligence. You understand the possibilities created by large language models (LLMs), machine learning (ML), natural language processing (NLP), autonomous workflows, and multi-agent architectures, and you want to apply them to mission-critical national security challenges.In today's contested and information-rich operating environment, military intelligence teams must rapidly make sense of large volumes of structured and unstructured data from multiple sources, formats, and domains. As an AI professional at Booz Allen, you'll help build intelligent systems that support intelligence discovery, analysis, prioritization, reporting, and decision advantage for defense and national security clients.On our team, you'll use your AI, data science, and sof tware development skills to create real-world mission impact. You'll work closely with clients, analysts, engineers, and mission stakeholders to understand operational needs, identify high-value use cases, and develop agentic AI capabilities that can reason over data, orchestrate workflows, retrieve relevant information, generate analytic products, and support human-in-the-loop decision-making. 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 ensure these systems are reliable, explainable, secure, testable, and aligned to operational requirements. Ultimately, you'll help military intelligence organizations use AI responsibly and effectively to accelerate insight, improve analytic tradecraft, and support informed decisions.Work with us as we develop advanced AI capabilities for the mission.Join us. The world can't wait.You Have:• Experience developing, integrating, or evaluating AI, ML, NLP, LLMs, or agentic AI capabilities for mission, operational, or enterprise use cases, and building AI-enabled applications using Python and modern AI / ML libraries or frameworks, including PyTorch, Scikit-Learn, LangChain, LlamaIndex, Hugging Face, or CUDA• Experience developing agentic AI systems, including autonomous or semi-autonomous agents, tool-using agents, multi-step reasoning workflows, task orchestration, retrieval-augmented generation, or human-in-the-loop AI capabilities• Experience analyzing, processing, and integrating structured and unstructured data sources, including intelligence data such as text, reports, messages, met adata, documents, or geospatial data• Experience designing, testing, validating, or evaluating AI/ML systems, including model performance, accuracy, relevance, robustness, hallucination mitigation, or mission-aligned evaluation criteria• Experience supporting military intelligence, defense intelligence, all-source analysis, targeting, indications and warning, collection management, operations intelligence, or national security missions, and developing AI systems for classified, air-gapped, secure, or operationally constrained environments• Experience with prompt engineering, prompt evaluation, model benchmarking, fine-tuning, synthetic data generation, or LLM application development• Knowledge of information retrieval, embeddings, vector databases, semantic search, data labeling, classification models, model evaluation, and data quality assessment• Ability to translate military intelligence mission requirements into technical AI solutions, prototypes, and production-ready capabilities• TS/SCI clearance• Bachelor's degree in Data Science, CS, AI, ML, Engineering, Operations Research, Applied Mathematics, or StatisticsNice If You Have:• Experience with distributed data, cloud, or high-performance computing tools, including Spark, Kafka, Hadoop, Hive, EMR, Databricks, Kubernetes, Docker, OpenSearch, Elasticsearch, or similar technologies• Experience developing APIs, microservices, analytic interfaces, dashboards, or production sof tware using FastAPI, Flask, REST services, Git, CI / CD, DevSecOps, Plotly, Dash, Streamlit, Tableau, or Power BI• Knowledge of intelligence tradecraft, analytic standards, military operations, Joint or Combatant Command environments, the intelligence cycle, AI safety, model governance, responsible AI, explainability, auditability, access control, or data security• Ability to collaborate with analysts, engineers, data owners, security teams, and mission stakeholders to deploy AI-enabled capabilities in operational environments• TS/SCI clearance with a polygraph• Master's degree in Data Science, CS, AI, ML, Engineering, Operations Research, Applied Mathematics, Statistics, or a related field• AI, ML, Cloud Computing, Data Engineering, Cybersecurity, or De #J-18808-Ljbffr

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