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Annotation Labelling Jobs in Maryland (NOW HIRING)

Linguist

California, MD · On-site

$35 - $40/hr

Develop and maintain annotation schemas and guidelines for LLM training data, including instruction-tuning, preference labeling, and RLHF. Evaluate and quality-check datasets for pre-training, fine ...

Annotation Labelling information

What is annotation labelling?

Annotation labelling is the process of tagging or marking data—such as images, text, or audio—with relevant information or labels. This is an essential step in preparing datasets for machine learning and artificial intelligence models, as it helps algorithms understand and learn from raw data. Annotation labelling can include tasks like identifying objects in photos, transcribing speech, or categorizing text. Skilled annotators ensure accuracy and consistency to improve model performance. People in this role often use specialized tools or software to streamline and standardize the annotation process.

What are the key skills and qualifications needed to thrive as an Annotation Labelling Specialist, and why are they important?

To thrive as an Annotation Labelling Specialist, you need strong attention to detail, data analysis capabilities, and familiarity with data annotation standards, usually supported by a background in computer science or related fields. Proficiency with annotation tools such as Labelbox, CVAT, or Supervisely, and sometimes knowledge of basic programming or scripting, is typically required. Excellent communication, consistency, and the ability to follow complex instructions are crucial soft skills for producing high-quality labeled data. These skills ensure the accuracy and reliability of datasets, which are foundational for successful machine learning and AI model development.

What are some common challenges faced by Annotation Labelling professionals, and how can they be managed?

Annotation Labelling professionals often encounter challenges such as maintaining high accuracy while handling repetitive data, meeting tight deadlines, and adapting to evolving project guidelines. To manage these, it’s important to develop strong attention to detail, regularly communicate with team leads to clarify instructions, and leverage annotation tools efficiently. Collaborating closely with quality assurance teams can also help identify and correct errors early, ensuring consistently high-quality outputs.

What is the difference between Annotation Labelling vs Data Labeling Specialist?

AspectAnnotation LabellingData Labeling Specialist
CredentialsBasic technical skills, attention to detailSimilar skills, sometimes additional domain knowledge
Work EnvironmentData annotation platforms, remote or officeData annotation tasks, often remote or in-office
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, healthcare, retail
Search & ComparisonCommonly compared for entry-level data tasksRelated but broader role

Annotation Labelling involves marking data such as images, text, or videos to train AI models. Data Labeling Specialists perform similar tasks but may have a broader scope, including verifying and managing labeled data. Both roles are essential in AI development, often overlapping in skills and work environment, but Annotation Labelling is more focused on the annotation process itself.

What are popular job titles related to Annotation Labelling jobs in Maryland? For Annotation Labelling jobs in Maryland, the most frequently searched job titles are:
What cities in Maryland are hiring for Annotation Labelling jobs? Cities in Maryland with the most Annotation Labelling job openings:

$35 - $40/hr

Other

Posted 17 days ago


Job description

Job Title: Linguist Location: Remote Duration: Contract - 12 months Pay Range: $35/hr $40/hr (W2) Job ID: 406613 About BCforward BCforward is a leading global IT consulting and workforce solutions firm providing services and support to Fortune 500 and government clients. Founded in 1998, BCforward has grown with our customers needs into a full-service business solutions provider. With delivery centers and offices across North America and India, we take pride in building long-term relationships and delivering excellence through innovation, collaboration, and integrity. Job Description We are seeking a Linguist II to join our dynamic team. The ideal candidate will have strong experience in linguistic data analysis, language technologies, and LLM/AI data operations and a proven ability to support data collection, synthetic data generation, annotation, and evaluation for LLM training, alignment, and AI agent development. Responsibilities: Apply linguistic expertise in syntax, semantics, pragmatics, and sociolinguistics to support LLM and generative AI systems. Collaborate with linguists, data operations teams, and ML engineers on data collection, curation, annotation, and localization for model training and fine-tuning. Develop and maintain annotation schemas and guidelines for LLM training data, including instruction-tuning, preference labeling, and RLHF. Evaluate and quality-check datasets for pre-training, fine-tuning, and alignment of language models. Support programmatic methods for generating synthetic annotated data at scale. Assist in model evaluation through prompt-based testing, red-teaming, and linguistic error analysis. Contribute to AI safety and responsible AI practices, including hallucination detection, bias identification, and tone and pragmatic review. Participate in experiments to assess data quality, annotation consistency, and downstream model performance. Required Skills & Qualifications: Bachelor's degree in Linguistics, Computational Linguistics, Computer Science, Speech Science, or related field. 1+ years of experience in Linguistics, Language Technologies, NLP, or AI/ML data operations, or equivalent. Native or near-native fluency in English and at least one additional language. Knowledge of syntax, semantics, pragmatics, sociolinguistics, and corpus linguistics. Familiarity with Large Language Models, including training data, evaluation, prompting, and fine-tuning practices. Exposure to LLM evaluation methodologies such as human evaluation, automated metrics, and adversarial testing. Experience with semantic ontologies, taxonomies, or intent/slot frameworks. Proficiency using AI agents and chatbots. Experience with database queries and data analysis processes such as SQL, spreadsheets, R, or Unix. Experience working with speech and text data in multiple languages. Comfort working in a fast-paced, collaborative environment with evolving priorities. Preferred Skills: Master's degree in Linguistics, Computational Linguistics, Language Technologies, or related field. Familiarity with ML frameworks and NLP libraries and tools, such as Hugging Face, spaCy, NLTK, or PyTorch. Exposure to statistical language modeling or training data pipelines. Strong organizational skills and attention to detail. Why BCforward? At BCforward, we believe in advancing lives and careers. When you join our team, you gain access to: Competitive compensation and benefits. Opportunities for growth with global clients. A supportive, inclusive culture that values innovation and people. Exposure to cutting-edge technologies and projects. About Our Commitment BCforward is an equal opportunity employer. We value diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, or veteran status. Interested? Apply Now! If this sounds like the right opportunity for you, please apply with your most recent resume.