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How much do ai data labeling jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for ai data labeling in Tennessee is $47.72, according to ZipRecruiter salary data. Most workers in this role earn between $17.95 and $70.61 per hour, depending on experience, location, and employer.

What is an AI data labeling?

An AI Data Labeling job involves annotating or tagging data (such as images, text, audio, or video) to train machine learning models. Labelers categorize, classify, or highlight data based on specific guidelines to help AI understand patterns and make accurate predictions. This process is crucial for supervised learning, where models learn from labeled examples. AI Data Labeling jobs are common in industries like healthcare, finance, and autonomous vehicles. Attention to detail and consistency are key skills for success in this role.

What does an AI data labeling do?

As an AI Data Labeling professional, your primary responsibilities include reviewing raw images, audio, or text data and accurately tagging or classifying them based on set guidelines provided by your employer. You may also be required to flag ambiguous cases or data anomalies and provide feedback to improve labeling instructions. Collaboration with data scientists or machine learning engineers is common to ensure your work aligns with project needs. Maintaining high accuracy while meeting productivity goals is essential for success in this role.

What are the key skills and qualifications needed to thrive in AI data labeling?

To thrive as an AI Data Labeling professional, you need strong attention to detail, analytical thinking, and the ability to follow precise guidelines, typically backed by a high school diploma or higher. Familiarity with annotation tools such as Labelbox, Supervisely, or internal labeling platforms, as well as basic understanding of data privacy practices, is often required. Patience, reliability, and good communication skills are important soft skills for consistently delivering high-quality labeled datasets and working effectively with team members. These skills ensure accurate data preparation for training AI models, directly impacting the model’s performance and the success of machine learning projects.

What are the most commonly searched types of Ai Data Labeling jobs in Tennessee?

The most popular types of Ai Data Labeling jobs in Tennessee are:

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For Ai Data Labeling jobs in Tennessee, the most frequently searched job titles are:

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Ai Data Labeling jobs near you
Infographic showing various Ai Data Labeling job openings in Tennessee as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $99,248 per year, or $47.7 per hour.

AI Data Center Infrastructure Deployment Specialist

Indus Group Inc

Memphis, TN • On-site

Other

Posted 7 days ago

Job description


AI Data Center Infrastructure Deployment Specialist

Location: Memphis, TN – Onsite with Travel

Work Arrangement: Onsite

Travel: Domestic and international travel may be required based on project needs

Position Summary

We are seeking an experienced Data Center Infrastructure Deployment Specialist to support the deployment, validation, troubleshooting, and operational readiness of physical infrastructure supporting large-scale AI data center environments. The ideal candidate will have hands-on experience with GPU/HPC infrastructure, servers, networking, cabling, storage, Linux, rack deployments, and data center operations.

This role requires a highly hands-on, operationally focused professional who can work effectively in fast-moving deployment environments, troubleshoot infrastructure issues, coordinate with multiple teams, and ensure deployments meet quality, safety, and operational standards.

What You'll Be Doing
  • Join a team responsible for building and scaling the physical infrastructure supporting new AI data center deployments.
  • Support operational readiness for new AI data center builds, expansions, and deployment projects.
  • Deploy physical infrastructure across new builds, expansions, and future deployments.
  • Install, inspect, validate, and troubleshoot servers, PDUs, network platforms, and related infrastructure.
  • Work with racks, switches, routers, storage systems, GPU components, and other data center hardware.
  • Execute deployment workstreams using established runbooks, rack maps, checklists, and validation workflows.
  • Work against client standards for rack and physical infrastructure readiness.
  • Follow deployment procedures, internal tools, and automation workflows to ensure network and infrastructure readiness.
  • Troubleshoot optic issues, hardware faults, cabling problems, deployment blockers, and link inconsistencies.
  • Troubleshoot Linux OS and network-adjacent issues during infrastructure deployment.
  • Work with contractors and internal teams to identify and correct build-quality issues and deployment problems.
  • Provide deployment support and respond to high levels of operational demand based on project requirements.
Responsibilities
  • Submit RMAs, track remote work requests, and manage shipping, receiving, and component inventory during deployment projects.
  • Provide clear status updates on assigned workstreams, including progress, blockers, risks, and estimated completion.
  • Partner with Data Center Operations, Network Engineering, Infrastructure Engineering, Logistics, Facilities, Security, and external vendors to support deployment readiness.
  • Support the handoff of deployed infrastructure into steady-state operations.
  • Participate in lessons-learned activities and contribute to improvements in runbooks, validation workflows, and deployment procedures.
  • Follow all safety, security, quality, and operational standards while working in active data center environments.
  • Independently execute standard deployment workstreams while maintaining high-quality standards.
  • Identify and resolve physical infrastructure issues, including incorrect labeling, improper cable routing, rack elevation mismatches, optic issues, and hardware placement errors.
  • Coordinate with contractors to correct deployment and build-quality issues.
  • Support project schedules, operational priorities, and deployment milestones in a fast-paced environment.
Required Qualifications
  • 5+ years of overall experience in infrastructure deployment, operations, or technical support.
  • 2+ years of hands-on experience deploying, operating, or supporting infrastructure in AI data centers, GPU/HPC environments, cloud environments, labs, networking, or technical operations.
  • Hands-on experience deploying and troubleshooting GPU servers, switches, storage systems, PDUs, optics, cabling, and related data center infrastructure.
  • Strong understanding of AI data center cabling standards, rack layouts, labeling practices, power paths, and physical deployment best practices.
  • Strong troubleshooting skills across hardware, cabling, Linux OS, and network connectivity.
  • Strong Linux command-line experience, including terminal sessions, logs, and standard diagnostic commands.
  • Familiarity with scripting, automation workflows, or tools used to validate hardware, cabling, and connectivity.
  • Ability to independently execute standard deployment workstreams with minimal supervision.
  • Ability to identify physical infrastructure issues such as deviations, incorrect labeling, improper cable routing, rack elevation mismatches, optic issues, and hardware placement errors.
  • Experience with inventory management, asset tracking, and RMA processes.
  • Strong verbal and written communication skills.
Preferred Skills
  • Experience supporting large-scale AI/GPU data center deployments.
  • Experience with GPU/HPC infrastructure and high-density rack environments.
  • Knowledge of data center networking, optics, structured cabling, and connectivity validation.
  • Experience working with contractors, vendors, and cross-functional engineering teams.
  • Familiarity with deployment runbooks, rack maps, checklists, and infrastructure validation processes.
  • Experience with automation and scripting for infrastructure validation and troubleshooting.
Additional Requirements
  • Ability to work onsite in Memphis, TN.
  • Willingness and ability to travel domestically and internationally as required by project needs.
  • Ability to work standard hours and support project-based rotations when required.
  • Valid driver's license and ability to drive as needed.
  • Ability to remain on your feet throughout the workday in an active data center environment.
  • Ability to lift and handle objects weighing up to 50 lbs.
  • Ability to work in a fast-moving environment with shifting priorities, tight timelines, and limited local support.
Core Competencies
  • Data Center Infrastructure Deployment
  • AI / GPU / HPC Infrastructure
  • Server & Hardware Deployment
  • Network & Structured Cabling
  • Linux Troubleshooting
  • Rack & Physical Infrastructure
  • Hardware & Connectivity Troubleshooting
  • RMA & Inventory Management
  • Deployment Validation
  • Runbooks & Operational Procedures
  • Cross-Functional Collaboration
  • Contractor/Vendor Coordination
  • Safety & Quality Compliance

Thanks & Regards

Mayank Chaudhary

Sr. Technical Recruiter (US Talent Acquisition)

Phone: +1 (907) 615-4847 (Ext. 3114)

Email: mayank@metablackllc.com

Meta Black LLC

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