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Data Annotation Tech Jobs in Silver Spring, MD (NOW HIRING)

Congensys Corp.

Senior Data Scientist

Woodlawn, MD · On-site

... annotation tools and semantic frameworks. • Ability to clean and process large amounts of real ... . • Industry experience preferred • Experience with, or the ability and willingness to learn ...

Seekr

Senior Data Scientist

Reston, VA · On-site

Coordinate data collection and annotation efforts for supervised training efforts * Design and ... Research and development on cutting-edge machine learning technologies Qualifications and Skills:

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All JobsData Annotation Tech JobsData Annotation Tech Jobs in Silver Spring, MD

Data Annotation Tech information

See Silver Spring, MD salary details

$12

$23

$36

How much do data annotation tech jobs pay per hour?

As of Jun 10, 2026, the average hourly pay for data annotation tech in Silver Spring, MD is $23.61, according to ZipRecruiter salary data. Most workers in this role earn between $17.40 and $28.08 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Data Annotation Tech position, and why are they important?

To thrive as a Data Annotation Tech, you need keen attention to detail, basic computer literacy, and familiarity with data labeling standards, often supported by a high school diploma or equivalent. Experience with annotation platforms, image or text labeling tools, and basic knowledge of data management systems is highly valuable. Strong organizational skills, patience, and effective communication set top candidates apart in this field. These skills and qualities ensure annotated data is accurate, consistent, and valuable for machine learning or AI projects.

What does a typical day look like for a Data Annotation Tech?

A typical day as a Data Annotation Tech involves reviewing large sets of data—such as images, text, or audio—and accurately labeling or categorizing them using specialized software. You may work independently or as part of a team, following specific project guidelines to ensure data integrity and consistency. Collaboration with project managers or data scientists is common when clarifying ambiguous data points or addressing annotation challenges. Additionally, productivity targets and quality checks are a regular part of the workflow, helping to keep projects on schedule and maintain high standards.

What is a Data Annotation Tech job?

A Data Annotation Tech is responsible for labeling and categorizing data, such as text, images, audio, or video, to train machine learning models. They follow specific guidelines to ensure accuracy and consistency in annotations, which helps improve the performance of AI systems. This role often involves repetitive tasks, attention to detail, and familiarity with various annotation tools. Data annotation is crucial for AI development in industries like healthcare, finance, and autonomous driving.

Is data annotation legit or not?

Data annotation is a legitimate job that involves labeling data such as images, text, or audio to train machine learning models. It is commonly performed remotely and requires attention to detail, basic technical skills, and familiarity with annotation tools. Many companies hire data annotators as part of AI development projects, making it a valid employment option.
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Data Annotation Tech jobs near you

Senior Data Scientist

ServIT Consulting LLC

Woodlawn, MD • On-site

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Key Required Skills:

  • Solid Experience with Natural Language Processing (NLP), Python, NLP frameworks, SQL, Pandas, NLTK and SPACy.
  • Experience with Generative AI and Large Language Models (LLM)
  • Excellent Communication skills

Position Description:

  • Hands on experience in Python, NLP frameworks, SQL, Pandas, NLTK, SPACy and LLMs
  • Well versed in SQL and analyzing trends and transactional data.
  • Understand real world challenges and develop automated data solutions
  • Develop, test, and deploy new techniques for NLP understanding
  • Scalable development/deployment of ML and Generative AI approaches (such as Large Language Models (LLMs)
  • Train and optimize NLP/LLM models and create Python based pipelines
  • Experience building cloud native solutions on AWS
  • Determine the nature of analytic problems, evaluate options, and offer recommendations for resolution.
  • Advise on the methods and data needed and/or available to evaluate the (intelligence or data) problem.
  • Collaborate with data collectors and analysts to identify and close gaps on complex monitoring problems.
  • Provide accurate, timely, complex, and sophisticated data analysis.

Skills Requirements:

Foundation for Success (Basic Qualifications)

  • Bachelor’s degree in Statistics, Applied Mathematics, Computer Science, or Information Science with industry experience on Python, NLP frameworks, SQL, Pandas, NLTK and SPACy, data science, and AI/ML/LLM engineering.
  • Overall 10+ years’ experience in IT industry

Factors To Help You Shine (Required Skills)

Selected candidate must be able to obtain and maintain a public trust clearance
Selected candidate must be willing to work on-site in Woodlawn, MD 5 days a week
Master''s and 10+ years of experience, Bachelor''s and 12+ years of experience or 18+ years in lieu of a degree

  • Solid Experience with Natural Language Processing (NLP), Python, NLP frameworks, SQL, Pandas, NLTK and SPACy.
  • Experience with Generative AI and Large Language Models (LLM)
  • Evidence of true self-starter and operating independently.
  • Fluency in Python Programming, version control and collaboration with GIT, standard Python packages (ex. Pandas, numpy, matplotlib) and ML frameworks
  • Knowledge of TensorFlow, PyTorch, Pandas, scikit-learn, NLTK, Azure ML (optional), Amazon Web Services EC2.
  • Experience with scalable data engineering frameworks such as Apache Spark and orchestration frameworks such as Airflow, and/or experience with semantic search.
  • Expert knowledge in conducting data analysis and applying advanced statistical concepts and ML methods to build, train, test, and evaluate a variety of supervised and unsupervised analytic models.
  • Experience with ML model deployment and operations like DevOps, MLOps, LLMOps.
  • Experience with NLP and Generative AI libraries like regular expressions (e.g., spacy, langchain), text annotation tools and semantic frameworks.
  • Ability to clean and process large amounts of real-world data.
  • Experience retrieving and manipulating data from a variety of data sources included DB2, Oracle, SQL Server, Hadoop and flat files.
  • Excellent Communication skills.
  • Experience with database management systems (e.g., PostgresSQL, MySQL, SQLite, SQL, etc.)
  • Excellent analytical skills to identify potential risks and propose effective solutions.
  • Excellent problem-solving skills, ability to collaborate with cross-functional teams and proven communication in written and verbal formats to various audiences to include executive leadership.

How To Stand Out From The Crowd (Desired Skills)

  • Prior experience with federal or state governments IT projects.
  • Industry experience preferred
  • Experience with, or the ability and willingness to learn distributed processing via the Hadoop ecosystem, i.e., Spark, Impala and Hive.
  • Experience working in an analytical research environment.
  • Experience in parallel processing such as GPU programming with CUDA
  • Experience with Mathematica
  • Experience using markup languages such as LaTeX, HTML, etc.
  • Experience with Natural Language Processing for anomaly detection

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