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Data Labeling Jobs in Virginia (NOW HIRING)

Data Scientist (Generative AI)

Mclean, VA · On-site +1

$125K - $160K/yr

We are looking for a more than just a "Data Scientist", but a technologist with excellent ... Identify, clean, label, and synthesize high-quality datasets for model training, fine-tuning, or ...

Data Scientist (Generative AI)

Mclean, VA · On-site

$125K - $160K/yr

We are looking for a more than just a "Data Scientist", but a technologist with excellent ... Identify, clean, label, and synthesize high-quality datasets for model training, fine-tuning, or ...

Knowledge of information retrieval, embeddings, vector databases, semantic search, data labeling, classification models, model evaluation, and data quality assessment * Ability to translate military ...

Strong Experience with ETL, data labeling, and data preparation * Experience with one or more of the following technologies: Cloudera, DataBricks, Snowflake, NiFi, Python, SQL, Kafka * Strong ...

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Data Labeling information

What are the key skills and qualifications needed to thrive in the Data Labeling position, 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.

What is a Data Labeling job?

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 is the job description of data labeling?

Data labeling involves annotating or tagging data such as images, text, or videos to help machine learning models understand and learn from the data. The role requires attention to detail, familiarity with labeling tools, and adherence to guidelines to ensure high-quality annotations. It is often performed remotely and may involve repetitive tasks with flexible schedules.

How much are data labelers paid?

Data labelers typically earn between $10 and $20 per hour, depending on experience, location, and the complexity of the labeling tasks. Many positions are freelance or remote, with pay rates varying across platforms and employers.

How do I become a data labeler?

To become a data labeler, you typically need basic computer skills, attention to detail, and the ability to follow instructions. Many positions require no formal degree and offer flexible, part-time schedules; familiarity with data annotation tools or platforms is often helpful. Applying through online job boards or company websites is common for entry-level roles.

Is data labelling a good career?

Data labeling is a common entry-level role in data annotation and machine learning workflows, often requiring attention to detail and basic computer skills. It can provide opportunities to develop skills in data management and AI, but typically offers lower pay and limited advancement without additional training or experience.
What are the most commonly searched types of Data Labeling jobs in Virginia? The most popular types of Data Labeling jobs in Virginia are:
What are popular job titles related to Data Labeling jobs in Virginia? For Data Labeling jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Data Labeling jobs in Virginia look for? The top searched job categories for Data Labeling jobs in Virginia are:
What cities in Virginia are hiring for Data Labeling jobs? Cities in Virginia with the most Data Labeling job openings:
Infographic showing various Data Labeling job openings in Virginia as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Data Scientist (Generative AI) with Security Clearance

Data Scientist (Generative AI) with Security Clearance

steampunk

Fairfax, VA • On-site

$125K - $160K/yr

Other

Re-posted 19 days ago


Job description

Overview We are looking for seasoned Data Scientist (Generative) to work with our existing team of Data Scientists and Engineers to use Generative AI technology in supporting Federal use cases. We are looking for a more than just a "Data Scientist", but a technologist with excellent communication and customer service skills and a passion for data and problem solving . Contributions * Design and train advanced machine learning models, especially generative models like GANs, VAEs, or transformer-based models. * Work closely with ML Engineers and Software Developers to transition models from a research and development stage to production. * Stay updated with the latest research and trends in AI to implement cutting-edge solutions. * Evaluate the performance of foundation al models (e.g., GPT, LLaMA , Claude) on domain-specific tasks and fine-tune them using supervised, reinforcement, or instruction tuning methods to align outputs with user needs and business goals. * Design and optimize prompts, few-shot examples, and system instructions to improve LLM behavior in constrained environments (e.g., RAG pipelines, multi-agent workflows, decision support systems). * Identify , clean, label, and synthesize high-quality datasets for model training, fine-tuning, or retrieval-augmented generation (RAG) . * Design experiments to evaluate generative model behavior (e.g., hallucination rates, factuality, coherence, safety), define appropriate benchmarks , and use metrics like BLEU, ROUGE, perplexity, and human evaluations. * Ability to leverage and integrate various data management tools at scale - cloud experience preferred * Support an Agile software development lifecycle * You will contribute to the growth of our AI & Data Exploitation Practice ! Qualifications Qualifications * Ability to hold a position of public trust with the US government. * Bachelor's degree in computer science, data science/statistics, information systems, engineering, business, or a scientific or technical discipline * 2-4 years industry experience developing ML/AI solutions and a passion for solving complex problems. * Must have hands-on experience in building and deploying generative models, with a portfolio of relevant projects * Must be proficient in Python, with strong coding practices for scalability and reproducibility. * Demonstrated experience in building, training, and deploying generative models like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), or autoregressive models like Transformer-based architectures. * Demonstrated experience manipulating structured and unstructured data for analysis * Demonstrated experience using AI frameworks like TensorFlow, PyTorch , Keras , or JAX. * Ability to implement and modify complex neural network architectures. * Skilled in using data manipulation and analysis libraries such as Pandas, NumPy, SciPy, and Scikit-learn. * Experience with model training, fine-tuning, and evaluation using frameworks like PyTorch or TensorFlow. * Deep knowledge of natural language processing techniques, including tokenization, embeddings, attention mechanisms, and prompt engineering. * Hands-on experience with large language models (e.g., GPT, LLaMA , Claude, Mistral) and associated libraries (e.g., Hugging Face Transformers). * Familiar with retrieval-augmented generation (RAG), data labeling, synthetic data generation, and data governance best practices. * Proficiency in Python and ML tooling (e.g., Jupyter , Git, Docker, APIs). Able to work in cross-functional teams to deliver AI capabilities into production environments, and write modular/reusable code. * Experience in Cloud analytics (AWS, Azure, or Google Cloud Platform - GCP) with tools such as AWS SageMaker , AWS Bedrock, Azure OpenAI, etc. * Experience with DevSecOps , as it applies to data science and MLOps * Data visualization skills in Tableau, Power BI, D3, ArcGIS , or similar are a plus * Experience with Elasticsearch, AWS Kendra, Azure Cognitive Search, or similar tool is a plus About steampunk Steampunk relies on several factors to determine salary, including but not limited to geographic location, contractual requirements, education, knowledge, skills, competencies, and experience. The projected compensation range for this position is $125,000 to $160,000. The estimate displayed represents a typical annual salary range for this position. Annual salary is just one aspect of Steampunk's total compensation package for employees. Learn more about additional Steampunk benefits here. Identity Statement As part of the application process, you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud. Steampunk is a Change Agent in the Federal contracting industry, bringing new thinking to clients in the Homeland, Federal Civilian, Health and DoD sectors. Through our Human-Centered delivery methodology, we are fundamentally changing the expectations our Federal clients have for true shared accountability in solving their toughest mission challenges. As an employee owned company, we focus on investing in our employees to enable them to do the greatest work of their careers - and rewarding them for outstanding contributions to our growth. If you want to learn more about our story, visit http://www.steampunk.com. We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law. Steampunk participates in the E-Verify program.