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Data Annotation For Ai Jobs in Baltimore, MD (NOW HIRING)

T. Rowe Price Associates, Inc.

AI Data Engineer

Baltimore, MD · Hybrid

$113K - $136K/yr

Join us for the opportunity to grow and make a difference in ways that matter to you. Role Summary T. Rowe Price is seeking an innovative Data AI Engineer to guide the development and deployment of ...

T Rowe Price

AI Data Engineer

Baltimore, MD · Hybrid

$113K - $136K/yr

AA Join us for the opportunity to grow and make a difference in ways that matter to you.A Role Summary T. Rowe Price is seeking an innovative Data AI Engineer to guide the development and deployment ...

BigBear.ai

Software Engineer (AI Infrastructure)

Columbia, MD · On-site

$170K - $201K/yr

Contribute to security best practices for AI systems and data * Provide technical guidance and informal mentorship to junior engineers What you need to have * 8+ years of relevant experience, or ...

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Data Annotation For Ai information

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

AspectData Annotation For AiData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech companies, AI projectsRemote or on-site, data processing companies
Industry UsageArtificial Intelligence, Machine LearningData management, content moderation
Job FocusPreparing data for AI algorithms through annotationLabeling data for various purposes, including AI

Data Annotation For Ai involves preparing datasets specifically for training AI models, focusing on detailed annotations. Data Labeler is a broader role that includes labeling data for multiple purposes, including AI but also other data management tasks. While both roles require similar skills, Data Annotation For Ai is more specialized towards AI development projects.

What is data annotation for AI?

Data annotation for AI is the process of labeling or tagging data—such as text, images, audio, or video—to make it understandable for machine learning models. Annotators add relevant information to raw data, helping AI systems learn to recognize patterns and make accurate predictions. This step is crucial for training, validating, and testing AI algorithms, especially in tasks like computer vision and natural language processing. High-quality data annotation directly impacts the effectiveness and reliability of AI applications.

What are the key skills and qualifications needed to thrive as a data annotation specialist for AI, and why are they important?

To thrive as a Data Annotation Specialist for AI, you need a keen eye for detail, a solid understanding of data labeling concepts, and often a background in the relevant domain (such as language, images, or audio). Proficiency with annotation platforms, data management systems, and basic familiarity with tools like Excel or Python can be highly valuable. Strong communication, consistency, and time management skills help ensure accuracy and meet project deadlines. These abilities are crucial because high-quality, well-annotated data is foundational for training reliable and effective AI models.

What are some common challenges faced by data annotators working on AI projects, and how can they be addressed?

Data annotators for AI often encounter challenges such as maintaining consistency across large datasets, understanding ambiguous labeling instructions, and managing repetitive tasks. To address these issues, it's important to actively seek clarification on guidelines, participate in team discussions to align on labeling standards, and use annotation tools that flag inconsistencies. Regular feedback sessions with project leads also help improve accuracy and efficiency, fostering a collaborative and supportive work environment.
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Data Annotation For Ai jobs near you
Infographic showing various Data Annotation For Ai job openings in Baltimore, MD as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Data Scientist [$231k/yr+] TS/SCI-FS Poly with Security Clearance

SYSTOLIC

Annapolis Junction, MD • On-site

$231K/yr

Other

Re-posted 21 days ago

Job description

Candidates must already possess an active Top Secret/SCI w/ Full Scope Polygraph to be considered. Summary: • Contribute to Natural Language Processing (NLP) projects, leveraging expertise in Human Language Processing (HLP). • Execute advanced language data tokenization and develop automated annotation solutions. • Enhance and refine existing Machine Learning/Artificial Intelligence (ML/AI) models by rigorously evaluating performance against human-generated benchmarks. • Apply Data Science methodologies to drive continuous improvement in language processing capabilities. Qualifications & Compensation: • Degree: Technical bachelor's degree or equivalent experience • Years of experience: 10+ years • Salary: $231k+ yearly compensation Job Description: • Lead the implementation and support of Natural Language Processing (NLP) initiatives. • Perform detailed language data tokenization and prepare data for model training. • Design, develop, and deploy automated solutions for efficient language data annotation, utilizing Machine Learning (ML) techniques. • Conduct rigorous performance evaluations of existing AI/ML models, comparing outputs against high-quality human annotations. • Utilize Data Science principles to analyze model performance metrics and identify areas for optimization. • Collaborate with cross-functional teams to integrate Human Language Processing (HLP) insights into broader projects. • Develop strategies for continuous model improvement and data quality enhancement. About SYSTOLIC: SYSTOLIC is dedicated to giving our employees the best possible company experience so that they can focus on providing outstanding support to their customer’s mission. Our company is founded on integrity, enthusiasm, and a relentless commitment to supporting the Intelligence Community. You can learn more about us and submit an application to be considered against our current and future openings at https://systolic.com. To learn about our compensation ranges, visit our Pay Transparency page at: https://systolic.com/pay-transparency

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