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Full Time Ai Data Annotation Jobs in Raleigh, NC

ServiceNow Capability Lead

Cary, NC · On-site

$14.75 - $19.50/hr

No Full time/Part time : Full-Time Project Only Hire : No Visa Sponsorship Available: No Why Black ... AI, data privacy, and governance alignment. Agile Delivery & Scrum Team Collaboration * Spend ...

AWS Python Data Architect

Raleigh, NC · On-site

$62 - $79.75/hr

... full-time Infosys employee you are also eligible for the following benefits: * Medical/Dental ... We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of ...

Cary, NC (Onsite) Employment Type: Full-Time Visa Type: USC / GC Only ✅ Must-Have Qualifications ... data engineering best practices ✔ Experience collaborating with cross-functional engineering, AI ...

Operations / Technology Reports to: VP of Marketing Type: Full-time Location: Raleigh, NC - on-site ... We're open to recent graduates from engineering, computer science, data, or AI programs who can ...

Operations / Technology Reports to: VP of Marketing Type: Full-time Location: Raleigh, NC - on-site ... We're open to recent graduates from engineering, computer science, data, or AI programs who can ...

AWS Redshift Data Engineer

Raleigh, NC · On-site

$111K - $133K/yr

EEO/About Us Benefits Along with competitive pay, as a full-time Infosys employee you are also ... We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of ...

AI Solutions Engineer

Raleigh, NC · On-site

$121K - $173K/yr

Job Type Full-time Description Since 2004, Vadum has built a brand known for practical innovation ... Build and support data ingestion pipelines, API integrations, agent frameworks, and evaluation ...

EEO/About Us Benefits Along with competitive pay, as a full-time Infosys employee you are also ... Collaborate with data scientists, software engineers, and product managers to define project ...

EEO/About Us Benefits Along with competitive pay, as a full-time Infosys employee you are also ... Collaborate with data scientists, software engineers, and product managers to define project ...

EEO/About Us Benefits Along with competitive pay, as a full-time Infosys employee you are also ... Collaborate with data scientists, software engineers, and product managers to define project ...

Showing results 41-60

Full Time Ai Data Annotation information

What is a full time AI data annotation job?

Full Time AI Data Annotation jobs involve labeling, tagging, or categorizing data such as images, text, audio, or video to help train machine learning models. Annotators play a crucial role in ensuring AI systems understand and process information accurately by providing high-quality, human-curated data. These positions usually require attention to detail, basic computer skills, and the ability to follow specific guidelines for different projects. Full-time roles typically offer stable hours and may be remote or on-site, depending on the employer.

What are the key skills and qualifications needed to thrive as a full time AI data annotation specialist?

To thrive as a Full Time AI Data Annotation Specialist, you need strong attention to detail, basic data literacy, and often a high school diploma or equivalent. Familiarity with annotation platforms (like Labelbox or Supervisely) and understanding of data labeling guidelines are typically required. Patience, consistency, and effective communication are soft skills that help ensure accuracy and clarity in collaborative projects. These skills and qualities are crucial for producing high-quality labeled data, which directly impacts the performance of AI models.

What are some common challenges faced by full time AI data annotation professionals, and how can they be addressed?

AI Data Annotation professionals often encounter challenges such as maintaining high accuracy while working with large datasets, interpreting ambiguous data, and consistently following complex labeling guidelines. These challenges can be addressed through thorough training, frequent communication with project managers or data scientists, and utilizing annotation tools with built-in quality checks. Collaboration with team members and regular feedback sessions also help ensure consistency and improve overall data quality, making the annotation process smoother and more efficient.

What is the difference between Full Time Ai Data Annotation vs Data Labeler?

AspectFull Time Ai Data AnnotationData Labeler
CredentialsHigh school diploma or equivalent; some roles prefer basic technical skillsHigh school diploma or equivalent; minimal technical requirements
Work EnvironmentOffice or remote; part of AI development teamsOffice or remote; often task-based or freelance
Industry UsageUsed across AI, machine learning, and data science industriesPrimarily in AI and machine learning industries for data preparation
Job ScopeFull-time, with responsibilities including data annotation, quality control, and collaborationTask-specific, focusing on labeling data accurately for AI training

Full Time Ai Data Annotation roles typically require more consistent hours, team collaboration, and a broader scope of responsibilities compared to Data Labelers, who often work on individual tasks with minimal oversight. Both roles are essential in AI development, but Full Time Ai Data Annotation offers more stability and integration within AI projects.

What are the most commonly searched types of Ai Data Annotation jobs in Raleigh, NC?

The most popular types of Ai Data Annotation jobs in Raleigh, NC are:

What are popular job titles related to Full Time Ai Data Annotation jobs in Raleigh, NC?

For Full Time Ai Data Annotation jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Full Time Ai Data Annotation jobs in Raleigh, NC look for?

The top searched job categories for Full Time Ai Data Annotation jobs in Raleigh, NC are:

Infographic showing various Full Time Ai Data Annotation job openings in Raleigh, NC as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

AI Solution Lead in Cary, NC (Fulltime, Onsite)

Northern Base

Cary, NC • On-site

Full-time

Re-posted 4 days ago


Job description

AI Solution Lead
Cary, NC
Fulltime, Onsite
 
Must Have Technical/Functional Skills
•  13+ years of experience with IT
• Build and productionize cloud native backend services and AI/LLM inference pipelines.
•  
• Design and develop Python-based APIs and microservices (FastAPI, async patterns) and agentic AI workflows using LangChain/LangGraph.
•  
• Implement and optimize LLM capabilities including embeddings, RAG, vector search, prompt/context engineering, and model versioning.
•  
• Package, serve, and monitor models for real-time and batch inference, ensuring operational readiness and performance.
•  
• Build event driven, resilient integrations and containerized services, with hands-on Kubernetes debugging and Helm-based deployments.
•  
• Establish observability, SLOs, CI/CD automation, testing
•  
• Apply strong systems design principles (concurrency, caching, reliability, rate limiting) and robust data engineering practices.
•  
• Cloud exposure preferred (Azure/AKS, managed services), with bonus experience in performance tuning, frontend collaboration, and model governance/monitoring.
Roles & Responsibilities
•  Build and productionize cloud native backend services and AI/LLM inference pipelines.
•  
• Design and develop Python-based APIs and microservices (FastAPI, async patterns) and agentic AI workflows using LangChain/LangGraph.
•  
• Implement and optimize LLM capabilities including embeddings, RAG, vector search, prompt/context engineering, and model versioning.
•  
• Package, serve, and monitor models for real-time and batch inference, ensuring operational readiness and performance.
•  
• Build event driven, resilient integrations and containerized services, with hands-on Kubernetes debugging and Helm-based deployments.
•  
• Establish observability, SLOs, CI/CD automation, testing
•  
• Apply strong systems design principles (concurrency, caching, reliability, rate limiting) and robust data engineering practices.
•  
• Cloud exposure preferred (Azure/AKS, managed services), with bonus experience in performance tuning, frontend collaboration, and model governance/monitoring.