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Data Annotation For Ai Jobs in Roxboro, NC (NOW HIRING)

Bitovi

AI Automation Engineer V

Durham, NC · Remote

$126K - $244K/yr

Bitovi has been engaged by Avalara to lead initial and technical interviews for this role. While ... You will partner with teams across Avalara to embed intelligent workflows, AI agents, and data ...

CREO

Senior Analyst- AI Engineer

Durham, NC · On-site +1

Draft requirements documents for AI prototypes and solutions, capturing functional specifications, data inputs, governance considerations, and user acceptance criteria. * Serve as a right hand to ...

CREO

Senior Analyst- AI Engineer

Durham, NC · Remote

Draft requirements documents for AI prototypes and solutions, capturing functional specifications, data inputs, governance considerations, and user acceptance criteria. * Serve as a right hand to ...

Bitovi

AI Automation Engineer V

Durham, NC · On-site +1

$126K - $244K/yr

Bitovi has been engaged by Avalara to lead initial and technical interviews for this role. While ... You will partner with teams across Avalara to embed intelligent workflows, AI agents, and data ...

Cisco

Applied AI Scientist

Durham, NC

Join the Foundational Modeling team at Splunk, where we advance the state of AI for highvolume, realtime, multimodal machinegenerated data - including logs, time series, traces, and events! We ...

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All JobsData Annotation For Ai JobsData Annotation For Ai Jobs in Roxboro, NC

Data Annotation For Ai information

What is the difference between Data Annotation For Ai vs Data Labeler?

AspectData Annotation For AiData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech companies, AI projectsRemote or on-site, data processing companies
Industry UsageArtificial Intelligence, Machine LearningData management, content moderation
Job FocusPreparing data for AI algorithms through annotationLabeling data for various purposes, including AI

Data Annotation For Ai involves preparing datasets specifically for training AI models, focusing on detailed annotations. Data Labeler is a broader role that includes labeling data for multiple purposes, including AI but also other data management tasks. While both roles require similar skills, Data Annotation For Ai is more specialized towards AI development projects.

What is data annotation for AI?

Data annotation for AI is the process of labeling or tagging data—such as text, images, audio, or video—to make it understandable for machine learning models. Annotators add relevant information to raw data, helping AI systems learn to recognize patterns and make accurate predictions. This step is crucial for training, validating, and testing AI algorithms, especially in tasks like computer vision and natural language processing. High-quality data annotation directly impacts the effectiveness and reliability of AI applications.

What are the key skills and qualifications needed to thrive as a data annotation specialist for AI, and why are they important?

To thrive as a Data Annotation Specialist for AI, you need a keen eye for detail, a solid understanding of data labeling concepts, and often a background in the relevant domain (such as language, images, or audio). Proficiency with annotation platforms, data management systems, and basic familiarity with tools like Excel or Python can be highly valuable. Strong communication, consistency, and time management skills help ensure accuracy and meet project deadlines. These abilities are crucial because high-quality, well-annotated data is foundational for training reliable and effective AI models.

What are some common challenges faced by data annotators working on AI projects, and how can they be addressed?

Data annotators for AI often encounter challenges such as maintaining consistency across large datasets, understanding ambiguous labeling instructions, and managing repetitive tasks. To address these issues, it's important to actively seek clarification on guidelines, participate in team discussions to align on labeling standards, and use annotation tools that flag inconsistencies. Regular feedback sessions with project leads also help improve accuracy and efficiency, fostering a collaborative and supportive work environment.

What cities near Roxboro, NC are hiring for Data Annotation For Ai jobs?

Cities near Roxboro, NC with the most Data Annotation For Ai job openings:

Data Annotation For Ai jobs near you

Senior Solutions Architect, AI Factory Deployment - NVIS

Nvidia

Durham, NC

Full-time

Posted 13 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 244 rated software companies

Job description

We are in search of a curious and motivated Senior Solutions Architect to join our NVIDIA Infrastructure Specialists team. In this capacity, you'll support the creation, implementation, and verification of AI factories, focusing on running and debugging AI/LLM workloads and benchmarks on Linux-based GPU clusters. You'll engage with NCCL and collectives like AllReduce and AllToAll to boost performance and scalability, receiving mentorship from senior architects on the team.


You will apply observability and automation to improve our benchmarking and validation efforts. You will be a key contact for troubleshooting workloads and benchmarks that fail, hang, or perform poorly. Additionally, you will collaborate with various NVIDIA teams to prepare AI factories for customers, validating both hardware and software for current AI applications.


What You Will Be Doing:

  • Set up, adjust, and verify AI factory environments across multi-GPU and multi-node Linux clusters.
  • Validate configurations against guidelines for NCCL, collectives, and distributed training frameworks.
  • Run key AI/LLM benchmarks - setup, orchestration, result collection, and analysis.
  • Investigate and address problems when training jobs or benchmarks fail, hang, or perform below expectations.
  • Build and improve observability for AI factories (metrics, logs, traces, dashboards) to understand workload behavior and system health.
  • Build automation using Python and Shell for conducting benchmarks, retrieving results, and completing regression checks.
  • Analyze communication patterns and NCCL usage for AI/LLM workloads, concentrating on collectives such as AllReduce and AllToAll.
  • Help identify and recommend improvements to job configuration, parallelism strategies, and cluster settings to improve throughput, latency, and scaling efficiency.
  • Work closely with hardware, software, networking, and product teams to prepare AI factories for customer use.
  • Contribute to documentation and readiness materials for internal and customer-facing teams.

What We Need to See:

  • Bachelor's degree or equivalent experience in Computer Science, Mathematics, Engineering, Physics, or a related field.
  • 5+ years of experience managing Linux-based systems in HPC, distributed systems, or AI/ML environments.
  • Hands-on experience running AI/ML workloads on multi-GPU and/or multi-node clusters, including some exposure to NCCL.
  • Practical knowledge of collective communication patterns like AllReduce and AllToAll, and their application in ML/LLM training.
  • Skilled in Python and Shell/Bash for scripting, automation, and tooling.
  • Strong communication skills and the ability to work effectively with cross-functional teams.

Ways to Stand Out From the Crowd:

  • Experience benchmarking distributed systems - crafting, running, and interpreting performance benchmarks.
  • Background in HPC performance engineering, SRE, or systems performance analysis for GPU-accelerated environments.
  • Familiarity with observability stacks (metrics/monitoring, logging, tracing) used for large distributed systems.
  • Experience building automation and CI-style pipelines for running and validating benchmarks at scale.
  • Demonstrated interest in using AI to solve practical problems, improve workflows, and guide data-driven decisions.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 4, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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