ZipRecruiter

Log In

1

Data Annotation Manager Jobs in Washington (NOW HIRING)

Gormat

Data Scientist 3

Annapolis Junction, MD · On-site

$132K - $147K/yr

Data Processing: (Data management and curation, data description and visualization, workflow and ... annotation of language data with parts of speech information, and improved existing models by ...

Gormat

Data Scientist 3

Annapolis Junction, MD · On-site

$132K - $147K/yr

Data Processing: (Data management and curation, data description and visualization, workflow and ... annotation of language data with parts of speech information, and improved existing models by ...

Axle

Data Scientist II

Rockville, MD

With experts in biomedical science, software engineering, and program management, we focus on ... annotation, DEG), and Digital Spatial Profiling (annotation, QC, normalization, spatial ...

Axle

Data Scientist II

Rockville, MD

With experts in biomedical science, software engineering, and program management, we focus on ... annotation, DEG), and Digital Spatial Profiling (annotation, QC, normalization, spatial ...

Axle

Data Scientist II

Rockville, MD · On-site

With experts in biomedical science, software engineering, and program management, we focus on ... annotation, DEG), and Digital Spatial Profiling (annotation, QC, normalization, spatial ...

Beyond SOF

DATA ENGINEER

Reston, VA · On-site

$119K - $143K/yr

Designs, implements, and operates data management systems for intelligence needs Designs how data ... Java -JDK 1.6+, Model View Controller (MVC) architecture, Annotation, Servelet 2.5/Java Server ...

next page

Showing results 1-20

All JobsData Annotation JobsData Annotation Manager JobsData Annotation Manager Jobs in Washington

Data Annotation Manager information

See Washington salary details

$35.1K

$110K

$194.8K

How much do data annotation manager jobs pay per year?

As of Jul 13, 2026, the average yearly pay for data annotation manager in Washington is $110,026.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,800.00 and $142,100.00 per year, depending on experience, location, and employer.

What is the salary of data annotation manager?

The salary of a data annotation manager typically ranges from $60,000 to $120,000 annually, depending on experience, location, and company size. Senior roles or those in high-cost areas may offer higher compensation, and familiarity with annotation tools and team management can influence pay levels.

How much do data annotation project managers make?

Data annotation project managers typically earn between $60,000 and $100,000 annually, depending on experience, location, and company size. They oversee annotation teams, coordinate workflows, and ensure quality standards are met, often requiring familiarity with annotation tools and project management skills.

What are some common challenges faced by Data Annotation Managers, and how can they be addressed?

Data Annotation Managers often encounter challenges such as maintaining high annotation quality across large and diverse datasets, managing a distributed team of annotators, and meeting tight project deadlines. To address these, it's important to implement robust quality assurance processes, provide ongoing training for annotators, and establish clear communication channels. Leveraging annotation tools with built-in validation features can also help ensure consistency and accuracy. Building a positive and collaborative team environment further contributes to better outcomes and workflow efficiency.

What does a Data Annotation Manager do?

A Data Annotation Manager oversees the process of labeling and categorizing data used to train machine learning models. They manage teams of annotators, ensure data quality, develop annotation guidelines, and coordinate with data scientists to meet project requirements. Their role is critical in maintaining high standards of accuracy and efficiency, as well as ensuring that datasets are properly prepared for AI and machine learning applications.

Does data annotation actually pay well?

Data annotation managers typically earn competitive salaries that reflect their experience and responsibilities, often ranging from entry-level to senior roles. Compensation can vary based on industry, location, and company size, with specialized skills in tools like labeling platforms and quality control often leading to higher pay.

What are the key skills and qualifications needed to thrive as a Data Annotation Manager, and why are they important?

To thrive as a Data Annotation Manager, you need expertise in data labeling processes, quality control, and a solid understanding of machine learning concepts, usually backed by a degree in computer science or a related field. Proficiency with annotation tools such as Labelbox, Supervisely, or CVAT, as well as experience with project management systems, is commonly required. Exceptional leadership, attention to detail, and strong communication skills help manage teams and ensure high annotation accuracy. These skills are critical for delivering reliable labeled datasets, which are essential for building effective AI and machine learning models.

How hard is it to get hired by data annotation?

Getting hired as a data annotation manager typically requires relevant experience in data labeling, familiarity with annotation tools, and strong organizational skills. The hiring process often involves reviewing previous work, technical assessments, and demonstrating attention to detail, with opportunities available in companies that outsource data labeling tasks.

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

AspectData Annotation ManagerData Labeling Specialist
CredentialsBachelor's degree in related field, experience in data managementHigh school diploma or equivalent, training in labeling tools
Work EnvironmentTeam management, project oversight, collaboration with data scientistsHands-on labeling work, using annotation tools, focused on data tagging
Industry UsageUsed in AI/ML projects for overseeing annotation teamsPerforms the actual data labeling tasks in machine learning workflows

The Data Annotation Manager oversees the entire annotation process, managing teams and ensuring quality, while the Data Labeling Specialist focuses on executing labeling tasks. Both roles are essential in AI/ML data preparation but differ in responsibilities and scope.

What are the most commonly searched types of Data Annotation jobs in Washington? The most popular types of Data Annotation jobs in Washington are:
What are popular job titles related to Data Annotation Manager jobs in Washington? For Data Annotation Manager jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Data Annotation Manager jobs in Washington look for? The top searched job categories for Data Annotation Manager jobs in Washington are:
What cities in Washington are hiring for Data Annotation Manager jobs? Cities in Washington with the most Data Annotation Manager job openings:
Data Annotation Manager jobs near you

Data Scientist 3

Gormat

Annapolis Junction, MD • On-site

$132K - $147K/yr

Full-time

Posted 6 days ago

Job description

We are seeking a Data Scientist proficient in Python and Jupyter Notebook to support a Natural Language Processing (NLP) project. You will help to accurately and automatically tokenize language data with spoken or written origins, develop automated solutions for the annotation of language data with parts of speech information, and improve existing models by scoring performance against human-generated annotations for speech and text.
The Level 3 Data Scientist shall possess the following capabilities:
  • Foundations: (Mathematical, Computational, Statistical).
  • Data Processing: (Data management and curation, data description and visualization, workflow and reproducibility).
  • Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations).
  • Ability to make and communicate principal conclusions from data using elements of mathematics, statistics, computer science, and applications-specific knowledge.
  • Ability to use analytic modeling, statistical analysis, programming, and/or another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique feature and limitations inherent in Government data holdings.
  • Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data.
  • Effectively communicate complex technical information to non-technical audiences.
  • DS position in X32 as a support for a Natural Language Processing (NLP) project to accurately and automatically tokenize language data with spoken or written origins; develop automated solutions for the annotation of language data with parts of speech information, and improved existing models by scoring performance against human-generated annotations for speech and text.

Qualifications:
  • Bachelor's Degree with 10 years of relevant experience, associate's degree with 12 years of experience may be considered for individuals with in-depth experience that is clearly related to the position.
  • Bachelor's Degree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science, Operations Research, or Computer Science or a degree in a related field (Computer Information Systems, Engineering), a degree in the physical/hard sciences (e.g. physics, chemistry, biology, astronomy), or other science disciplines with a substantial computational component (i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g. algorithms, programming, , data structures, data mining, artificial intelligence). College-level requirement, or upper-level math courses designated as elementary or basic do not count.
  • Broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university.
  • Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least on high level language (e.g. Python), statistical analysis (e.g. variability, sampling error, inference, hypothesis testing, EDA, application of linear models), data management (e.g. data cleaning and transformation), data mining, data modeling and assessment, artificial intelligence, and/or software engineering.

TS/SCI with polygraph is required.

Apply