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Data Labelling Jobs in Dallas, TX (NOW HIRING)

Tesla

Data Labeler Manager

Dallas, TX · On-site

What to Expect The Data Labeling team is responsible for annotating images, videos, and other data for our Tesla AI software. Accurate data is the foundation for training our neural networks and ...

Waabi

Senior Software Engineer, Auto Labelling

Dallas, TX · On-site +1

$170K - $220K/yr

... labelling system leveraging computer vision, and machine learning. - Manage the end-to-end ... Bonus/nice to have: - Familiarity with 3D data (LIDAR/Point Clouds) and multi-modal sensor fusion ...

Waabi

Senior Software Engineer, Auto Labelling

Dallas, TX · On-site +1

$170K - $220K/yr

... labelling system leveraging computer vision, and machine learning. - Manage the end-to-end ... Bonus/nice to have: - Familiarity with 3D data (LIDAR/Point Clouds) and multi-modal sensor fusion ...

Waabi

Senior Software Engineer, Auto Labelling

Dallas, TX · On-site +1

$170K - $220K/yr

... labelling system leveraging computer vision, and machine learning. - Manage the end-to-end ... Bonus/nice to have: - Familiarity with 3D data (LIDAR/Point Clouds) and multi-modal sensor fusion ...

The Peak Organization

Data Center Technician

Dallas, TX · On-site

$30 - $35/hr

Organize, route, and label data and power cables to maintain a clean, efficient, and safe environment, adhering to industry standards. * Transceiver Installation : Install, test, and troubleshoot ...

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Data Labelling information

See Dallas, TX salary details

$45.5K

$163.2K

$240.9K

How much do data labelling jobs pay per year?

As of Jul 4, 2026, the average yearly pay for data labelling in Dallas, TX is $163,241.00, according to ZipRecruiter salary data. Most workers in this role earn between $132,100.00 and $168,200.00 per year, depending on experience, location, and employer.

What does a data labeler do?

A data labeler is responsible for annotating and categorizing data such as images, videos, or text to help train machine learning models. They use tools and guidelines to ensure accurate labeling, which is essential for developing reliable AI systems. Attention to detail and understanding of the data are important for this role.

Is data labelling a good career?

Data labelling is a common entry-level role in data annotation and machine learning workflows, often requiring attention to detail and familiarity with labeling tools. It can offer flexible schedules and opportunities to develop skills in AI and data management, but typically involves repetitive tasks and lower pay compared to more advanced tech roles.

What is a Data Labelling job?

A Data Labelling job involves annotating data, such as text, images, audio, or video, to help train machine learning models. Labelers categorize or tag data by following specific guidelines to ensure accuracy and consistency. This process is essential for improving AI applications, including image recognition, natural language processing, and autonomous systems. Attention to detail and adherence to instructions are key skills required for this role.

What is the job description of data labeling?

Data labeling involves annotating or tagging data such as images, text, or videos to help machine learning models understand and learn from the data. The role requires attention to detail, familiarity with labeling tools, and adherence to guidelines to ensure high-quality annotations for AI training. It is often performed remotely and may involve repetitive tasks with a focus on accuracy.

What are the typical daily responsibilities of a Data Labelling professional?

Data Labelling professionals are generally responsible for reviewing and accurately annotating large volumes of data—such as images, audio, video, or text—to support machine learning and AI projects. This often involves using specialized labeling platforms and following detailed guidelines provided by data scientists or project managers. You may also participate in regular team meetings to discuss quality standards or address ambiguities in data, and your work is typically reviewed for accuracy before being integrated into training datasets. Collaborating with other data annotators, engineers, and analysts is a common part of the process to ensure consistency and high-quality results.

What are the key skills and qualifications needed to thrive in the Data Labelling position, and why are they important?

To thrive as a Data Labelling professional, you need strong attention to detail, proficiency with data annotation processes, and a basic understanding of machine learning concepts. Familiarity with annotation tools like Labelbox, Supervisely, or Amazon SageMaker Ground Truth is often required, and some roles may value certifications in data processing or AI fundamentals. Reliability, patience, and the ability to follow precise instructions are important soft skills for success in this position. These skills ensure accurate and consistent data labeling, which is critical for developing effective AI models and maintaining data integrity.

How can I get started in data labeling?

To start in data labeling, gain familiarity with annotation tools like Labelbox or CVAT and understand data privacy requirements. Basic skills in image, text, or audio annotation are helpful, and some roles may require attention to detail and the ability to follow guidelines. Entry-level positions often provide training, making it accessible for beginners.
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Data Labelling jobs near you
Data Labeler Manager

Data Labeler Manager

Tesla

Dallas, TX • On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 17 days ago

Tesla rating

8.5

Company rating: 8.5 out of 10

Based on 669 frontline employees who took The Breakroom Quiz

1st of 44 rated automakers

Job description

What to Expect

The Data Labeling team is responsible for annotating images, videos, and other data for our Tesla AI software. Accurate data is the foundation for training our neural networks and serves as the ground truth for Tesla's artificial intelligence. The team works cohesively with engineering teams to launch customer-facing releases.

The Data Labeler Manager will lead a team of Data Labelers that labels in 3D image data for neural network training. A successful candidate will have high attention to detail, an appreciation for data integrity, leadership skills to drive efficiency for medium-sized teams of annotators and adhere to clear instructions directed by leadership to deliver results.

What You'll Do
  • Conduct ongoing performance management: create coaching plans, track progress, conduct monthly 1:1's, and complete monthly analyst reports
  • Evaluate daily performance in proprietary software to report daily summaries and team metrics to ensure the team is consistently exceeding expectations
  • Work directly with engineers and Tesla AI leadership and own annotation policies that require an understanding of both technical and operational constraints
  • Have a solid understanding of project guidelines to be able to communicate labeling concepts effectively, labeling inefficiencies, assist in creating documentation and training materials
  • Execute proper headcount allocation between quality control, labeling, and prioritize job queues daily as directed by leadership
  • Ensure documentation and daily planning for the team is accurate and consistently updated
  • Ensure team alignment with company policies
  • Other supervisory duties such as employee development, conducting bi-yearly performance reviews and monthly performance check-ins with Team Leads and Data Labelers, and accurately manage timekeeping

What You'll Bring
  • Experience managing and motivating medium-sized teams that perform manual operations
  • Ability to manage time efficiently, prioritizing tasks by order of precedence and completing in a timely manner
  • Proven record of accomplishments executing and meeting sensitive deadlines with experience managing multiple competing projects with limited resources
  • Strong problem-solving skills, with an aptitude for quickly learning systems with minimal training and can adapt in an ambiguous environment
  • Effective communication and presentation skills - can explain complicated topics and ideas in a clear and concise manner
  • Commitment to data accuracy and throughput

Compensation and Benefits Benefits

Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:

  • Medical plans > plan options with $0 payroll deduction
  • Family-building, fertility, adoption and surrogacy benefits
  • Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution
  • Company Paid (Health Savings Accounts) HSA Contribution when enrolled in the High-Deductible medical plan with HSA
  • Healthcare and Dependent Care Flexible Spending Accounts (FSA)
  • 401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits
  • Company paid Basic Life, AD&D
  • Short-term and long-term disability insurance (90 day waiting period)
  • Employee Assistance Program
  • Sick and Vacation time (Flex time for salary positions, Accrued hours for Hourly positions), and Paid Holidays
  • Back-up childcare and parenting support resources
  • Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance
  • Weight Loss and Tobacco Cessation Programs
  • Tesla Babies program
  • Commuter benefits
  • Employee discounts and perks program

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