ZipRecruiter

Log In

1

Manager Ai Annotation Jobs in Virginia (NOW HIRING)

Seekr

Senior Data Scientist

Reston, VA

... AI/ML concepts into practical language * Manage machine learning algorithm lifecycle * Support pre ... Coordinate data collection and annotation efforts for supervised training efforts * Design and ...

Seekr

Senior Data Scientist

Reston, VA · On-site

... AI/ML concepts into practical language * Manage machine learning algorithm lifecycle * Support pre ... Coordinate data collection and annotation efforts for supervised training efforts * Design and ...

AgileEngine

Taxonomy Analyst ID76178

Richmond, VA · On-site

... management, content classification, data validation, or data labeling/annotation; - Strong ... AI tools (e.g., ChatGPT, Gemini, Claude) for data curation or evaluation. PERKS AND BENEFITS ...

AgileEngine

Taxonomy Analyst

Richmond, VA · On-site

... management, content classification, data validation, or data labeling/annotation; * Strong ... Hands-on experience working with LLMs / AI tools (e.g., ChatGPT, Gemini, Claude) for data curation ...

next page

Showing results 1-20

All JobsAi Annotation JobsManager Ai Annotation JobsManager Ai Annotation Jobs in Virginia

Manager Ai Annotation information

What is the difference between Manager Ai Annotation vs Data Annotator?

AspectManager Ai AnnotationData Annotator
Required CredentialsBachelor's degree in related field, experience in AI projectsHigh school diploma or equivalent, on-the-job training
Work EnvironmentTeam management, project oversight, collaboration with data scientistsData labeling tasks, working with annotation tools
Industry UsageAI development, machine learning projectsData preparation for AI models
Search & Comparison IntentUnderstanding managerial roles in AI annotationEntry-level annotation tasks

The main difference between Manager Ai Annotation and Data Annotator lies in their responsibilities and experience. Managers oversee annotation projects, coordinate teams, and ensure quality, requiring leadership skills and experience. Data Annotators focus on labeling data accurately under supervision. Managers typically have higher credentials and work in strategic roles, while annotators perform the hands-on labeling tasks essential for AI training.

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

Staff AI Engineer with Security Clearance

BlackSky Holdings, Inc

Herndon, VA • On-site

Other

Posted 28 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.

Apply