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Data Annotation Manager Jobs in Washington (NOW HIRING)

DATA ENGINEER

Reston, VA ยท 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 ...

Federal AI Engineer

Fort Belvoir, VA ยท On-site

$138K - $153K/yr

... data discovery, ETL/ELT processes to ingest structured data/annotation processes to enrich ... Define, monitor, and report key business metrics to management; design, implement, and manage ...

Data Scientist 3

Annapolis, MD ยท On-site

$161K - $211K/yr

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

Department of Health and Human Services (DHHS) agencies to develop data science solutions to ... Experience in content development and/or text annotation (e.g., annotation of certain types of ...

Department of Health and Human Services (DHHS) agencies to develop data science solutions to ... Experience in content development and/or text annotation (e.g., annotation of certain types of ...

Department of Health and Human Services (DHHS) agencies to develop data science solutions to ... Experience in content development and/or text annotation (e.g., annotation of certain types of ...

Department of Health and Human Services (DHHS) agencies to develop data science solutions to ... Experience in content development and/or text annotation (e.g., annotation of certain types of ...

Showing results 41-60

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 Sep 14, 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 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.

What are the key skills and qualifications needed to thrive as a data annotation manager?

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.

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 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 cities in Washington are hiring for Data Annotation Manager jobs?

Cities in Washington with the most Data Annotation Manager job openings:

Infographic showing various Data Annotation Manager job openings in Washington as of August 2026, with employment types broken down into 84% Full Time, 7% Part Time, and 9% Contract. Highlights an 69% In-person, 7% Hybrid, and 24% Remote job distribution, with an average salary of $110,026 per year, or $52.9 per hour.

DATA ENGINEER

Reston, VA โ€ข On-site

Beyond SOF
Professional, Scientific, and Technical Servicesย โ€ขย 11 - 50 employees

$119K - $143K/yr

Full-time

Re-posted 20 days ago


Job description

Essential Job Responsibilities:
Designs, implements, and operates data management systems for intelligence needs
Designs how data will be stored, accessed, used, integrated, and managed by different data regimes and digital systems.
Works with data users to determine, create, and populate optimal data architectures, structures, and systems.
Plans, designs, and optimizes data throughput and query performance.
Participates in the selection of backend database technologies (e.g. SQL, NoSQL, HPC, etc.), their configuration and utilization, and the optimization of the full data pipeline infrastructure to support the actual content, volume. ETL, and periodicity of data to support the intended kinds of queries and analysis to match expected responsiveness ..
Serves as the technical representative present during all deployments to address any technical or security issues.
Advises government principals as to the potential implications of said solutions.
Assists with ensuring certification for new releases are presented to the Change Advisory Board.
Coordinates activities, monitor progress, interact with UNIT personnel and Chief Information Office (CIO) personnel to meet requirements in achieving certification and authorization to release updates on NETWORK
Possesses a general understanding of the business cycle associated with conventional arms purchase transactions and various IC message traffic systems
Possesses the ability to visually display quantitative information
Applies the following technical skills to develop an ORACLE database and PostgreSQL database and enhance its capabilities:
Java -JDK 1.6+, Model View Controller (MVC) architecture, Annotation, Servelet 2.5/Java Server Pages (JSP) 2.2, Servlet Filters, Java Server Pages Standard Tag Library (JSTL)
Web-HTML, Javascript, Dynamic HTML (DHTML) and Asynchronous Javascript and XML (AJAX)
Open Source APls -Struts (MVC framework), Hibernate (Object Relational Mapping (ORM), persistence, caching, searching), iText (PDF generation). POI (MS Excel generation), JFreeChart (graphs & charts), Simple (XML serialization), Display Tag (table generation)
Database-ORACLE 12. l.0.2vl3 database and PostgreSQL 11.1-Rl database (or most recent version), maintenance. tuning and configuration
Email -JavaMail
Security -Java Cryptography Extensions/Java Secure Socket Extension (JCE/JSSE) APL DoDIIS Public Key Infrastructure (PKI), HTTPS/SSL programming and configuration, CAPCO (rules and automated parsing or validation). Access Controls: Role Base Access Controls (RBAC), Mandatory Access Control (MAC) and Discretionary Access Control (DAC), PL3 security and auditing requirements
Web/App Server-Apache Tomcat 7+
AWS Certification: Our FOMA initiative relies heavily on Amazon Web Services (AWS) infrastructure
Clearance: AN ACTIVE TS/SCI with CI scope polygraph is required