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Data Annotation Engineer Jobs in Washington (NOW HIRING)

With experts in biomedical science, software engineering, and program management, we focus on ... Develop benchmark datasets, annotation guidelines, and evaluation pipelines for scientific ...

Software Engineers own userfacing features endtoend: slick React/NextJS interfaces, performant Node ... Design delightful data workflow such as instant search, realtime diffing, collaborative annotation ...

Coordinate data collection and annotation efforts for supervised training efforts * Design and ... Strong programming skills in Python required. Experience in java and html a plus. * Experience ...

Coordinate data collection and annotation efforts for supervised training efforts * Design and ... Strong programming skills in Python required. Experience in java and html a plus. * Experience ...

Senior Machine Learning Engineer

Mclean, VA

$107K - $147K/yr

Experience with data curation/annotation workflows and dataset quality control. * Software engineering: Python (NumPy, scipy, pandas/polars), PyTorch (preferred) or TensorFlow, git, CI/CD pipelines ...

Senior Machine Learning Engineer

Mclean, VA

$105K - $145K/yr

Experience with data curation/annotation workflows and dataset quality control. * Software engineering: Python (NumPy, scipy, pandas/polars), PyTorch (preferred) or TensorFlow, git, CI/CD pipelines ...

Software Engineer Washington, DC State Affairs is the nation's leading news and policy intelligence ... Design delightful data workflow such as instant search, real-time diffing, collaborative annotation ...

Software Engineer

Washington, DC · On-site

$120K - $180K/yr

Software Engineers own user-facing features end-to-end: slick React/Next JS interfaces, performant ... Design delightful data workflow such as instant search, real-time diffing, collaborative annotation ...

Staff AI Engineer About Us: BlackSky is a real-time intelligence company. We own and operate the ... Collaborate with the Data QA team to define annotation standards, resolve taxonomy issues, and ...

Staff AI Engineer About Us: BlackSky is a real-time intelligence company. We own and operate the ... Collaborate with the Data QA team to define annotation standards, resolve taxonomy issues, and ...

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Showing results 1-20

Data Annotation Engineer information

See Washington salary details

$58.3K

$167K

$223.1K

How much do data annotation engineer jobs pay per year?

As of Jun 22, 2026, the average yearly pay for data annotation engineer in Washington is $167,014.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,100.00 and $222,000.00 per year, depending on experience, location, and employer.

What are the main challenges faced by Data Annotation Engineers in their daily work?

One of the main challenges Data Annotation Engineers face is ensuring consistent accuracy and quality in labeling large and often complex datasets. Attention to detail is critical, as even small errors can significantly affect machine learning model performance. Additionally, engineers must frequently adapt to evolving annotation guidelines and emerging data types, which requires ongoing learning and flexibility. Collaboration with data scientists and project managers is common to clarify requirements and resolve ambiguities, making strong communication skills essential for success.

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

To thrive as a Data Annotation Engineer, you need a strong background in data analysis, attention to detail, and familiarity with annotation processes, often supported by a degree in computer science or a related field. Proficiency with annotation tools like Labelbox, CVAT, or VIA, and understanding of data formats used in machine learning, is commonly required. Excellent communication, collaboration, and organizational skills help you effectively manage projects and cooperate with cross-functional teams. These abilities are crucial for delivering high-quality labeled data, which directly impacts the performance of AI and machine learning models.

Is data annotation real or fake?

Data annotation is a real and essential process in machine learning where human annotators label data such as images, text, or audio to train AI models. Data annotation engineers perform this work using specialized tools and quality standards to ensure accurate and reliable datasets.

What is a data annotation engineer?

A data annotation engineer is a professional responsible for labeling and annotating data, such as images, text, or videos, to train machine learning models. They often use specialized tools and follow guidelines to ensure data quality and accuracy, supporting AI development and data-driven applications.

How hard is it to get a job with data annotation tech?

Getting a job as a Data Annotation Engineer typically requires basic computer skills, attention to detail, and familiarity with annotation tools or platforms. Entry-level positions are often accessible with minimal formal education, but having knowledge of machine learning concepts or experience with data labeling can improve job prospects.

Does data annotation really pay you?

Data annotation engineers are typically paid for their work, often earning hourly wages or project-based fees depending on the employer or platform. Compensation varies based on experience, skill level, and the complexity of annotation tasks, which may involve using tools like labeling software or AI platforms.

What is a Data Annotation Engineer job?

A Data Annotation Engineer is responsible for labeling and annotating data—such as text, images, audio, or video—to train machine learning models. They ensure that data is accurately categorized and structured to improve model performance. This role often involves using specialized annotation tools, following detailed guidelines, and working closely with data scientists and AI teams. Data Annotation Engineers play a crucial role in the development of AI applications by providing high-quality labeled datasets for supervised learning.

What are popular job titles related to Data Annotation Engineer jobs in Washington? For Data Annotation Engineer jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Data Annotation Engineer jobs in Washington look for? The top searched job categories for Data Annotation Engineer jobs in Washington are:
What cities in Washington are hiring for Data Annotation Engineer jobs? Cities in Washington with the most Data Annotation Engineer job openings:
Infographic showing various Data Annotation Engineer job openings in Washington as of June 2026, with employment types broken down into 71% Full Time, 6% Part Time, and 23% Contract. Highlights an 78% In-person, and 22% Remote job distribution, with an average salary of $167,014 per year, or $80.3 per hour.

Data Science Fellow - AI/NLP

Axle

Rockville, MD

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 12 days ago


Job description

(ID: 2026-2316)

Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).

Benefits We Offer:

  • 100% Medical, Dental & Vision Coverage for Employees
  • Paid Time Off and Paid Holidays
  • 401K match up to 5%
  • Educational Benefits for Career Growth
  • Employee Referral Bonus
  • Flexible Spending Accounts:
    • Healthcare (FSA)
    • Parking Reimbursement Account (PRK)
    • Dependent Care Assistant Program (DCAP)
    • Transportation Reimbursement Account (TRN)

We are seeking a postdoctoral researcher to develop AI/NLP and knowledge engineering methods that transform biomedical literature, experimental protocols, and source evidence into structured, quarriable, and evidence-grounded knowledge for organoid protocol standardization and optimization.

The postdoc will work at the intersection of large language models, biomedical NLP, scientific document understanding, knowledge graphs, ontology grounding, computational biology, and human-in-the-loop curation. Potential projects include LLM-based protocol extraction, retrieval-augmented literature mining, curated knowledge graph construction, ontology and entity normalization, protocol comparison, consensus protocol derivation, benchmark design, and natural-language interfaces over structured biological knowledge.

Responsibilities

  • Design and implement AI/NLP methods for biomedical literature mining and structured protocol knowledge extraction.

  • Develop benchmark datasets, annotation guidelines, and evaluation pipelines for scientific information extraction.

  • Build and evaluate RAG, in-context learning, fine-tuning, graph matching, entity normalization, and KG query workflows.

  • Analyze extraction errors, model behavior, retrieval failures, grounding quality, and biological ambiguity.

  • Collaborate with software engineers to integrate research methods into usable tools and reproducible pipelines.

  • Collaborate with organoid biologists and domain experts to translate biological protocol knowledge into computable representations.

  • Prepare manuscripts, conference abstracts, technical reports, design documents, and open-source research artifacts.

  • Help define research milestones, evaluation criteria, and publication strategy for protocol intelligence work.

Required Qualifications

  • PhD in computer science, computational biology, bioinformatics, biomedical informatics, NLP, machine learning, data science, or a related field.

  • Strong Python programming skills.

  • Demonstrated research experience with NLP, information extraction, LLMs, RAG, transformers, structured prediction, or scientific text mining.

  • Ability to design controlled computational experiments, create benchmark datasets, and analyze results rigorously.

  • Familiarity with biological, biomedical, or scientific data.

  • Strong written communication skills and interest in publishing methods-oriented research.

  • Comfort working with complex, evolving research codebases and interdisciplinary teams.

Preferred Qualifications

  • Experience with scientific document processing, PDF parsing, biomedical literature mining, or methods-section extraction.

  • Experience with knowledge graphs, ontologies, graph databases, graph algorithms, or semantic data modeling.

  • Hands-on experience with fine-tuning LLMs, LoRA/QLoRA, Hugging Face, PyTorch, or API-based model evaluation.

  • Hands-on experience with prompt engineering, structured JSON extraction, schema validation, tool use, or agentic LLM workflows.

  • Hands-on experience with RAG systems, vector search, graph-augmented retrieval, or natural-language query over structured data.

  • Exposure to bioinformatics concepts (e.g., sequence alignment, clustering, or phylogenetic analysis) that can inform protocol comparison and similarity methods.

  • Background in stem cell biology, organoids, developmental biology, wet-lab protocols, or biological assays, enabling more effective collaboration with domain experts.

Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.

The diversity of Axle's employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.

Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate's experience, qualifications, skills, and location.

Salary Range
$90,000—$100,000 USD