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Data Annotation Services Jobs in Silver Spring, MD

BAE Systems

INTEL ANALYST

Fort Belvoir, VA · On-site

Responsibilities for this position include providing imagery and geospatial analysis services in ... Experience with Machine Learning training data creation, annotation, and review as well as ...

BAE Systems

INTEL ANALYST

Fort Belvoir, VA

Responsibilities for this position include providing imagery and geospatial analysis services in ... Experience with Machine Learning training data creation, annotation, and review as well as ...

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

Data Annotation Services information

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

To excel in Data Annotation Services, strong attention to detail, data literacy, and a foundational understanding of data labeling processes are essential, often requiring a high school diploma or equivalent. Familiarity with annotation platforms, labeling tools, and sometimes basic knowledge of scripting or data management systems is typically expected. Strong work ethic, consistency, and effective communication skills help individuals stand out in collaborative, deadline-driven environments. These capabilities ensure high-quality, accurate labeled data, which is critical for training reliable machine learning models.

What is the difference between Data Annotation Services vs Data Labeling Specialists?

AspectData Annotation ServicesData Labeling Specialists
CredentialsTypically no formal credentials required; focus on trainingOften have training in specific tools or industry standards
Work EnvironmentCollaborative, often remote or in-office teamsSimilar, working in teams or independently on labeling tasks
Industry UsageUsed by AI/ML companies for training datasetsEmployed in similar settings, focusing on labeling data for AI models
Search & Comparison IntentUnderstanding services offered for data preparationLooking for roles or tasks related to data labeling

Data Annotation Services encompass the broader process of preparing and annotating data for AI and machine learning projects, often provided by specialized companies. Data Labeling Specialists are individual professionals or team members who perform the actual labeling tasks within these services. While both are closely related, services refer to the overall offering, whereas specialists are the personnel executing the work.

What are some common challenges faced when working in data annotation services, and how can I address them?

In data annotation services, one common challenge is maintaining consistency and accuracy, especially when handling large datasets or ambiguous data points. Clear annotation guidelines and regular communication with team leads help ensure that everyone interprets the data similarly. Additionally, repetitive tasks can lead to fatigue, so it's important to take scheduled breaks and leverage available annotation tools to streamline workflows. Collaborating with peers to discuss edge cases also helps improve overall data quality and fosters a supportive team environment.

What are data annotation services?

Data annotation services involve labeling or tagging data—such as images, text, audio, or video—to make it understandable for machine learning models. These services are essential in training artificial intelligence systems to recognize patterns, objects, or other relevant information in raw data. Companies use data annotation to improve the accuracy and effectiveness of AI applications, such as self-driving cars, chatbots, and image recognition. Professional annotators or specialized platforms often perform these tasks to ensure high-quality, consistent results.
What are popular job titles related to Data Annotation Services jobs in Silver Spring, MD? For Data Annotation Services jobs in Silver Spring, MD, the most frequently searched job titles are:
What job categories do people searching Data Annotation Services jobs in Silver Spring, MD look for? The top searched job categories for Data Annotation Services jobs in Silver Spring, MD are:
What cities near Silver Spring, MD are hiring for Data Annotation Services jobs? Cities near Silver Spring, MD with the most Data Annotation Services job openings:
Data Annotation Services jobs near you
Infographic showing various Data Annotation Services job openings in Silver Spring, MD as of June 2026, with employment types broken down into 75% Full Time, and 25% Part Time. Highlights an 100% In-person job distribution.

Senior Data Scientist

Omm IT Solutions

Ellicott City, MD

Contractor

Posted 14 hours ago

Job description

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PLEASE NOTE:<\/b><\/span><\/span><\/u>
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  • It is 100% onsite position in Woodlawn, MD.<\/b>
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  • Candidate should be local and ready to work on onsite 5 days a week at Client HQ in Woodlawn, MD.<\/b><\/span><\/span><\/span>
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  • Candidate must be able to obtain and maintain a public trust clearance<\/b>
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  • <\/b><\/span><\/span> <\/b><\/span><\/span><\/span>Interviews will be scheduled quickly for early next week. There will only be one round of interview<\/b><\/span><\/span><\/span>
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    Position Description:<\/b><\/span><\/span><\/u>
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    • Hands on experience in Python, NLP frameworks, SQL, Pandas, NLTK, SPACy and LLMs
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    • Well versed in SQL and analyzing trends and transactional data.
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    • Understand real world challenges and develop automated data solutions
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    • Develop, test, and deploy new techniques for NLP understanding
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    • Scalable development\/deployment of ML and Generative AI approaches (such as Large Language Models (LLMs)
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    • Train and optimize NLP\/LLM models and create Python based pipelines
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    • Experience building cloud native solutions on AWS
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    • Determine the nature of analytic problems, evaluate options, and offer recommendations for resolution.
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    • Advise on the methods and data needed and\/or available to evaluate the (intelligence or data) problem.
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    • Collaborate with data collectors and analysts to identify and close gaps on complex monitoring problems.
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    • Provide accurate, timely, complex, and sophisticated data analysis.
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      Key Required Skills:<\/b><\/span><\/span><\/u>
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      • Solid Experience with Natural Language Processing (NLP), Python, NLP frameworks, SQL, Pandas, NLTK and SPACy.
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      • Experience with Generative AI and Large Language Models (LLM)
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      • Excellent Communication skills.
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        Requirements<\/h3>\n
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        Skills Requirements:<\/b><\/span><\/span><\/span>
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        Basic Qualification:<\/b><\/span><\/span><\/span><\/u>
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        • Master's and 10+ years of experience, Bachelor's and 12+ years of experience or 18+ years in lieu of a degree<\/span><\/span><\/span>
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        • 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.<\/span><\/span><\/span>
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        • Overall 10+ years' experience in IT industry<\/span><\/span><\/span>
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          Required Skills:<\/b><\/span><\/span><\/span><\/u>
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          • Solid Experience with Natural Language Processing (NLP), Python, NLP frameworks, SQL, Pandas, NLTK and SPACy.<\/span><\/span><\/span>
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          • Experience with Generative AI and Large Language Models (LLM)<\/span><\/span><\/span>
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          • Evidence of true self\-starter and operating independently.<\/span><\/span><\/span>
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          • Fluency in Python Programming, version control and collaboration with GIT, standard Python packages (ex. Pandas, numpy, matplotlib) and ML frameworks<\/span><\/span><\/span>
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          • Knowledge of TensorFlow, PyTorch, Pandas, scikit\-learn, NLTK, Azure ML (optional), Amazon Web Services EC2.<\/span><\/span><\/span>
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          • Experience with scalable data engineering frameworks such as Apache Spark and orchestration frameworks such as Airflow, and\/or experience with semantic search.<\/span><\/span><\/span>
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          • 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.<\/span><\/span><\/span>
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          • Experience with ML model deployment and operations like DevOps, MLOps, LLMOps.<\/span><\/span><\/span>
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          • Experience with NLP and Generative AI libraries like regular expressions (e.g., spacy, langchain), text annotation tools and semantic frameworks.<\/span><\/span><\/span>
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          • Ability to clean and process large amounts of real\-world data.<\/span><\/span><\/span>
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          • Experience retrieving and manipulating data from a variety of data sources included DB2, Oracle, SQL Server, Hadoop and flat files.<\/span><\/span><\/span>
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          • Excellent Communication skills.<\/span><\/span><\/span>
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          • Experience with database management systems (e.g., PostgresSQL, MySQL, SQLite, SQL, etc.)<\/span><\/span><\/span>
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          • Excellent analytical skills to identify potential risks and propose effective solutions.<\/span><\/span><\/span>
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          • 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.<\/span><\/span><\/span>
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            Desired Skills:<\/b><\/span><\/span><\/span><\/u>
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            • Prior experience with federal or state governments IT projects.<\/span><\/span><\/span>
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            • Industry experience preferred<\/span><\/span><\/span>
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            • Experience with, or the ability and willingness to learn distributed processing via the Hadoop ecosystem, i.e., Spark, Impala and Hive.<\/span><\/span><\/span>
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            • Experience working in an analytical research environment.<\/span><\/span><\/span>
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            • Experience in parallel processing such as GPU programming with CUDA<\/span><\/span><\/span>
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            • Experience with Mathematica<\/span><\/span><\/span>
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            • Experience using markup languages such as LaTeX, HTML, etc.<\/span><\/span><\/span>
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            • Experience with Natural Language Processing for anomaly detection<\/span><\/span><\/span>.
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