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Data Annotation Engineer Jobs in Washington (NOW HIRING)

State Affairs

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 ...

BlackSky

Staff Engineer, AI

Herndon, VA · On-site +1

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 ...

BlackSky

Staff Engineer, AI

Herndon, VA · On-site

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 ...

TIAG

Software Test Automation Engineer

Reston, VA · On-site +1

$48 - $63.25/hr

Perform verification across all layers, including Frontend (UI), Backend (API/Services), and Data ... Experience in applying strategies that utilize annotation in/near code for automated generation of ...

Beyond SOF

Full Stack Developer (Java Developer)

Reston, VA · On-site

$54.50 - $70.50/hr

... Data Engineer with full stack developer experience and oracle database experience to help us ... Java -JDK 1.6+, Model View Controller (MVC) architecture, Annotation, Servelet 2.5/Java Server ...

Beyond SOF

Full Stack Developer (Java Developer)

Reston, VA · On-site

$54.50 - $70.50/hr

... Data Engineer with full stack developer experience and oracle database experience to help us ... Java -JDK 1.6+, Model View Controller (MVC) architecture, Annotation, Servelet 2.5/Java Server ...

Vets2PM

CAD/Revit Drafter - Level II

Arlington, VA · On-site

$42.50 - $52/hr

... from engineers and project managers. * Convert legacy CAD or MicroStation files into Revit ... Support data integration efforts by attaching project attributes and relevant metadata to model ...

Vets2PM

CAD/Revit Drafter - Level II

Arlington, VA

$42.50 - $52/hr

... engineers and project managers. Convert legacy CAD or MicroStation files into Revit, ensuring ... Support data integration efforts by attaching project attributes and relevant metadata to model ...

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Data Annotation Engineer information

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$58.3K

$167K

$223.1K

How much do data annotation engineer jobs pay per year?

As of Jun 1, 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 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 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.

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.
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Data Annotation Engineer jobs near you

Staff AI Engineer with Security Clearance

BlackSky Holdings, Inc

Herndon, VA • Remote

Other

Posted 13 days ago

Job description

BlackSky is seeking a Staff AI Engineer to lead the architecture, development, and delivery of mission-critical AI solutions within customer environments. This is a hands-on role and an opportunity to develop and shape an exciting new growth area. The ideal candidate for this role blends deep technical ownership (roadmap, R&D, AI/ML systems) with customer-facing solution delivery (scoping, prototype-to-production, and executive communication).

This senior individual contributor role will partner with CV, MLOps, Data QA, Solutions, and BD teams to ensure BlackSky delivers reliable and actionable insights. The role will be full-time based out of Herndon, VA working in our SCIF with occasional customer site commitments and will report to the Senior Manager of AI. Responsibilities: Partner with CV and MLOps to design and extend components needed to ensure models are trained, versioned, deployed, monitored, and maintained reliably in customer environments.

Collaborate with the Data QA team to define annotation standards, resolve taxonomy issues, and identify data-quality improvements based on model failure modes. Independently prototype, evaluate, and deploy AI capabilities in a secure development environment. Communicate technical strategy, progress, risks, and opportunities clearly to leadership, cross-functional partners, and other stakeholders.

Contribute to proposals, white papers, and long-term strategy, shaping future mission-aligned geospatial AI investments. Own and architect the mission-aligned roadmap for geospatial CV and applied AI, partnering with customers to translate mission requirements into technical designs and implementing core components. Other job-related duties as assigned.

Required Qualifications: Minimum of 10 years of hands-on software engineering experience, including at least 4+ years developing and deploying applied AI/ML systems and pipelines. Bachelor’s degree in CS/EE/math/statistics or a related quantitative field. Strong proficiency in Python and modern ML/CV libraries such as PyTorch or TensorFlow.

Experience researching, building, and evaluating production-ready CV models for detection, segmentation, change detection, or related tasks. Experience working with remote sensing imagery including geometry, radiometric normalization, augmentation, and sensor-specific challenges. Hands-on experience with geospatial tools such as GDAL, Rasterio, GeoPandas, Shapely, xarray, or Zarr.

Experience with modern ML infrastructure, including cloud services (e.g., AWS), containerization and orchestration platforms (e.g., Kubernetes), and the ability to adapt these systems to customer-specific or offline environments such as secure enclaves, on-prem systems, or air-gapped deployments. Strong ability to communicate complex technical concepts to diverse audiences including leadership and technical teams. Must have an active US Top Secret clearance with an SCI.

Preferred Qualifications: M.S. or Ph.D. in CS/EE/math/statistics or a related quantitative field.

At least 2 years of experience designing, building, and operating AI/ML systems in secure, on-prem and/or air-gapped systems. Experience working in DoD, IC, or Fed/Civ environments. Experience designing and executing large-scale CV experiments, including dataset construction, synthetic/augmented data generation, and evaluation protocols tailored to mission needs.

Familiarity with remote sensing data sources including BlackSky, Airbus, Planet, and Vantor. Demonstrated experience designing CV/ML systems and pipelines that meet or exceed benchmarks and are optimized for production constraints such as latency and efficiency. Exposure to foundation models, VLMs, and other multimodal approaches for geospatial imagery.

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