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Data Annotation Manager Jobs in Dallas, TX (NOW HIRING)

Tesla

Data Labeler Manager

Dallas, TX · On-site

... and own annotation policies that require an understanding of both technical and operational ... Data Labelers, and accurately manage timekeeping Qualifications : Required : • Experience ...

HumanSignal

Delivery Lead

Dallas, TX · Remote

$110K - $140K/yr

Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery. We design and create datasets from scratch, recruit and manage ...

HumanSignal

High Volume (TOFU) Recruiter

Dallas, TX · On-site +1

$55K - $100K/yr

Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery. We design and create datasets from scratch, recruit and manage ...

AgileEngine

Taxonomy Analyst ID76178

Dallas, TX · On-site

... management, content classification, data validation, or data labeling/annotation; - Strong analytical skills, exceptional attention to detail, and sharp pattern recognition abilities; - Proven ...

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All JobsData Annotation JobsData Annotation Manager JobsData Annotation Manager Jobs in Dallas, TX

Data Annotation Manager information

See Dallas, TX salary details

$30.7K

$96.1K

$170.2K

How much do data annotation manager jobs pay per year?

As of Jul 26, 2026, the average yearly pay for data annotation manager in Dallas, TX is $96,140.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,300.00 and $124,200.00 per year, depending on experience, location, and employer.

What is the salary of data annotation manager?

The salary of a data annotation manager typically ranges from $60,000 to $120,000 annually, depending on experience, location, and company size. Senior roles or those in high-cost areas may offer higher compensation, and familiarity with annotation tools and team management can influence pay levels.

How much do data annotation project managers make?

Data annotation project managers typically earn between $60,000 and $100,000 annually, depending on experience, location, and company size. They oversee annotation teams, coordinate workflows, and ensure quality standards are met, often requiring familiarity with annotation tools and project management skills.

What are some common challenges faced by Data Annotation Managers, and how can they be addressed?

Data Annotation Managers often encounter challenges such as maintaining high annotation quality across large and diverse datasets, managing a distributed team of annotators, and meeting tight project deadlines. To address these, it's important to implement robust quality assurance processes, provide ongoing training for annotators, and establish clear communication channels. Leveraging annotation tools with built-in validation features can also help ensure consistency and accuracy. Building a positive and collaborative team environment further contributes to better outcomes and workflow efficiency.

What does a Data Annotation Manager do?

A Data Annotation Manager oversees the process of labeling and categorizing data used to train machine learning models. They manage teams of annotators, ensure data quality, develop annotation guidelines, and coordinate with data scientists to meet project requirements. Their role is critical in maintaining high standards of accuracy and efficiency, as well as ensuring that datasets are properly prepared for AI and machine learning applications.

Does data annotation actually pay well?

Data annotation managers typically earn competitive salaries that reflect their experience and responsibilities, often ranging from entry-level to senior roles. Compensation can vary based on industry, location, and company size, with specialized skills in tools like labeling platforms and quality control often leading to higher pay.

What are the key skills and qualifications needed to thrive as a Data Annotation Manager, and why are they important?

To thrive as a Data Annotation Manager, you need expertise in data labeling processes, quality control, and a solid understanding of machine learning concepts, usually backed by a degree in computer science or a related field. Proficiency with annotation tools such as Labelbox, Supervisely, or CVAT, as well as experience with project management systems, is commonly required. Exceptional leadership, attention to detail, and strong communication skills help manage teams and ensure high annotation accuracy. These skills are critical for delivering reliable labeled datasets, which are essential for building effective AI and machine learning models.

How hard is it to get hired by data annotation?

Getting hired as a data annotation manager typically requires relevant experience in data labeling, familiarity with annotation tools, and strong organizational skills. The hiring process often involves reviewing previous work, technical assessments, and demonstrating attention to detail, with opportunities available in companies that outsource data labeling tasks.

What is the difference between Data Annotation Manager vs Data Labeling Specialist?

AspectData Annotation ManagerData Labeling Specialist
CredentialsBachelor's degree in related field, experience in data managementHigh school diploma or equivalent, training in labeling tools
Work EnvironmentTeam management, project oversight, collaboration with data scientistsHands-on labeling work, using annotation tools, focused on data tagging
Industry UsageUsed in AI/ML projects for overseeing annotation teamsPerforms the actual data labeling tasks in machine learning workflows

The Data Annotation Manager oversees the entire annotation process, managing teams and ensuring quality, while the Data Labeling Specialist focuses on executing labeling tasks. Both roles are essential in AI/ML data preparation but differ in responsibilities and scope.

What are the most commonly searched types of Data Annotation jobs in Dallas, TX? The most popular types of Data Annotation jobs in Dallas, TX are:
What are popular job titles related to Data Annotation Manager jobs in Dallas, TX? For Data Annotation Manager jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Data Annotation Manager jobs in Dallas, TX look for? The top searched job categories for Data Annotation Manager jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Data Annotation Manager jobs? Cities near Dallas, TX with the most Data Annotation Manager job openings:
Data Annotation Manager jobs near you
Infographic showing various Data Annotation Manager job openings in Dallas, TX as of July 2026, with employment types broken down into 2% Locum Tenens, 35% Full Time, 25% Part Time, 2% Contract, 35% Nights, and 1% Summer. Highlights an 56% Physical, 1% Hybrid, and 43% Remote job distribution, with an average salary of $96,140 per year, or $46.2 per hour.
Technical Product Manager (Data Collection & Pipeline)

Technical Product Manager (Data Collection & Pipeline)

Caterpillar

Irving, TX • On-site

$160K - $185K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago

Caterpillar Inc. rating

7.5

Company rating: 7.5 out of 10

Based on 474 frontline employees who took The Breakroom Quiz

264th of 485 rated machine equipment manufacturers

Job description

Career Area:
Technology, Digital and Data
Job Description:
Your Work Shapes the World at Caterpillar Inc.
When you join Caterpillar, you're joining a global team who cares not just about the work we do - but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here - we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it.
Job Summary:
As the Technical Product Manager for Data Collection & Pipeline, you will be responsible for defining and executing the strategy, roadmap, and delivery of data products that enable AI, machine learning, analytics, and autonomous systems development. This role owns the end-to-end data ecosystem, including data collection, data acquisition strategies, annotation and labeling operations, data quality frameworks, and scalable data pipelines.
What You Will Do:
Maximize the value of enterprise data assets and define work for multiple scrum teams supporting data collection, labeling, quality, and pipeline initiatives. Collaborate with Product Owners, System Engineering, Data Scientists, Machine Learning Engineers, Data Architects, Analytics Architects, and Platform Architects to own and progressively elaborate functional and non-functional Epics and Features for Development Teams to deliver. The Technical Product Manager is empowered to make all decisions regarding the Data Product Backlog.
  • Responsible for creating, maintaining, and prioritizing the Data Product Backlog according to business value, data readiness needs, model performance requirements, and operational priorities for the life of the product.
  • Act as the key decision-maker regarding data collection capabilities, labeling workflows, data quality requirements, and pipeline functionality.
  • Owns definition of acceptance criteria for data products, features, datasets, and platform capabilities.
  • Responsible for defining data collection strategies that support AI, machine learning, analytics, and software product development.
  • Lead prioritization of data acquisition, sensor data collection, simulation data generation, and data sourcing initiatives.
  • Drive development and optimization of labeling and annotation workflows
  • Partner with engineering teams to define and deliver scalable data ingestion, transformation, validation, storage, and delivery pipelines.
  • Establish and monitor data quality metrics, governance standards, and operational KPIs to ensure datasets meet customer and business requirements.
  • Represent internal and external customers by understanding data requirements and translating them into actionable product capabilities.
  • Communicates data platform releases, roadmap updates, and capability enhancements to stakeholders and customers.
  • Employee is also responsible for performing other job duties as assigned by Caterpillar management from time to time.

What You Will Have:
  • Business Analysis: Knowledge of business analysis and the set of tasks, techniques, and tools required to identify business and data needs; ability to recommend solutions that deliver value to stakeholders through scalable data products and services.
  • Decision Making and Critical Thinking: Knowledge of the decision-making process and associated tools and techniques; ability to accurately analyze data-related challenges and reach productive decisions based on informed judgment, balancing quality, cost, scalability, and business value.
  • Effective Communications: Understanding of effective communication concepts, tools, and techniques; ability to effectively transmit, receive, and accurately interpret ideas, information, and needs across engineering, data science, operations, leadership, vendors, and customers
  • Data Product Business Knowledge: Knowledge of and experience with the business aspects and operation of data products and platforms; ability to manage data assets, current uses, future requirements, and long-term data strategy.
  • Data Collection and Labelling Operations: Knowledge of data collection methodologies, data acquisition strategies, annotation and labeling workflows, data quality management, and operational processes required to create high-quality datasets.
  • Data Engineering and Pipeline Development: Knowledge of data engineering methodologies, modern data architectures, ETL/ELT processes, cloud-based data platforms, and scalable data pipeline best practices.

Consideration For Top Candidates:
  • Lead enterprise-scale data programs from strategy development through roadmap execution and operationalization.
  • At least 8 years of experience in Product Management, Technical Product Management, Data Product Management, or related software leadership roles.
  • Experience defining and executing data collection, data acquisition, labeling, and data pipeline strategies.
  • Strong understanding of dataset lifecycle management, data quality frameworks, governance, and operational metrics.
  • Experience working closely with Data Engineering, Machine Learning, Analytics, and Platform teams.
  • Data analytics and commercializing data products or APIs.

Additional Details:
  • This position requires the candidate to work full-time at the Irving, TX office (Dallas)
  • Domestic relocation assistance is available for this position.
  • Visa sponsorship is NOT available with this position.

Summary Pay Range:
$128,470.00 - $208,770.00
Compensation and benefits offered may vary depending on multiple individualized factors, job level, market location, job-related knowledge, skills, individual performance and experience. Please note that salary is only one component of total compensation at Caterpillar.
Benefits:
Subject to plan eligibility, terms, and guidelines. This is a summary list of benefits.
  • Medical, dental, and vision benefits*
  • Paid time off plan (Vacation, Holidays, Volunteer, etc.)*
  • 401(k) savings plans*
  • Health Savings Account (HSA)*
  • Flexible Spending Accounts (FSAs)*
  • Health Lifestyle Programs*
  • Employee Assistance Program*
  • Voluntary Benefits and Employee Discounts*
  • Career Development*
  • Incentive bonus*
  • Disability benefits
  • Life Insurance
  • Parental leave
  • Adoption benefits
  • Tuition Reimbursement

* These benefits also apply to part-time employees
This position requires working onsite five days a week.
Relocation is available for this position.
Visa Sponsorship is not available for this position.
Posting Dates:
July 20, 2026 - August 3, 2026
Any offer of employment is conditioned upon the successful completion of a drug screen.
Caterpillar is an Equal Opportunity Employer, Including Veterans and Individuals with Disabilities. Qualified applicants of any age are encouraged to apply.
Not ready to apply? Join our Talent Community.

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