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Freelance Machine Learning Data Annotation Jobs in Dallas, TX

YO AI Labs

AI Data Science Expert - Remote

Dallas, TX · Remote

$100 - $200/hr

... Annotation * Data Interpretation * Fact Checking * Independent Research * Problem-Solving * Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning ...

New

YO AI Labs

AI Data Scientist Expert - Remote

Dallas, TX · Remote

$100 - $200/hr

... Annotation * Data Interpretation * Fact Checking * Independent Research * Problem-Solving * Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning ...

New

Expert Technology Services

Data Annotator

Irving, TX · On-site

$109K - $132K/yr

Support the development of autonomous mining machines by executing manual data annotation, sensor data fusion, and rigorous QA review, creating high-quality datasets for advanced AI models ...

Expert Technology Services

Data Annotator

Irving, TX · On-site

$109K - $132K/yr

... data annotation and quality assurance (QA) review for perception and VLA (Vision-Language-Action) data, including video, images, and multi-sensor machine data. - Annotate mining site entities (e.g ...

Expert Technology Services

Data Annotator

Irving, TX · On-site

$109K - $132K/yr

... annotation and rigorous QA review for perception (video, images, sensor data) and VLA (Vision ... machinery) in 2D video and 3D LiDAR/radar data. - Track and map heavy equipment trajectories ...

Expert Technology Services

Data Annotator

Irving, TX · On-site

$109K - $132K/yr

Perception annotation: video, images, machine sensor data that describe objects, 3D, trajectory, etc VLA annotation: task, action, intent, chain of causation, outcomes Build the brain behind the ...

Expert Technology Services

Data Annotator

Irving, TX · On-site

... Data Annotation & QA Review - Annotate and QA review multi-modal data: video, images, 3D point clouds, and machine sensor data (LiDAR, radar, CAN bus). - Label objects, 3D spatial boundaries ...

Expert Technology Services

Data Annotator

Irving, TX · On-site

... annotation and QA review for perception (video, images, 3D sensor data) and Vision-Language-Action (VLA) tasks. - Label 2D and 3D spatial data, including video, images, LiDAR, radar, and machine ...

Confie

Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

... data warehouse platform using the Snowpark framework Develop novel solutions using knowledge of the latest artificial intelligence/machine learning/natural language processing techniques and rigorous ...

Highbrow LLC

Data Scientist / ML Engineer

Frisco, TX · On-site

$100 - $130/hr

Data Scientist / ML Engineer Year Of Experience : 7+ years Location: Overland Park KS/ Frisco TX ( ... Expertise with scaling pilot machine learning solutions to a large scale production environment ...

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Freelance Machine Learning Data Annotation information

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How much do freelance machine learning data annotation jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for freelance machine learning data annotation in Dallas, TX is $21.63, according to ZipRecruiter salary data. Most workers in this role earn between $17.12 and $24.71 per hour, depending on experience, location, and employer.

What is the difference between Freelance Machine Learning Data Annotation vs Data Labeler?

AspectFreelance Machine Learning Data AnnotationData Labeler
CredentialsBasic understanding of annotation tools, sometimes with specialized domain knowledgeTypically no formal credentials required
Work EnvironmentRemote, flexible, project-basedOften remote or in-house, depending on employer
Industry UsageUsed in AI/ML development for training datasetsUsed in data preparation for various industries, including AI
Search/Comparison IntentFocuses on freelance opportunities, project scope, and toolsMore general, often employed by companies for data labeling tasks

Freelance Machine Learning Data Annotation involves independently completing annotation tasks for AI models, often with specialized tools and domain knowledge. Data Labelers typically perform similar tasks but may work as employees or contractors within a company. The main difference lies in the freelance nature and project-based work of data annotation roles.

What are the key skills and qualifications needed to thrive as a freelance machine learning data annotation specialist?

To thrive as a Freelance Machine Learning Data Annotation specialist, you need attention to detail, basic knowledge of data labeling concepts, and familiarity with machine learning data types. Experience with annotation tools (such as Labelbox, RectLabel, or CVAT) and understanding of data privacy protocols are commonly required. Strong communication, time management, and the ability to follow complex guidelines are essential soft skills for delivering accurate results. These skills ensure high-quality, consistent data annotation, which is critical for effective machine learning model training and performance.

What is freelance machine learning data annotation?

Freelance machine learning data annotation involves labeling or tagging data—such as images, text, audio, or video—to help train machine learning models. As a freelancer, you work independently or through platforms, completing specific annotation tasks assigned by companies or researchers. This work is essential because high-quality labeled data is required for AI systems to learn and make accurate predictions. Annotators may categorize images, transcribe speech, or highlight relevant information in documents. The flexibility of freelancing allows you to choose projects and work remotely.

What are some common challenges faced by freelance machine learning data annotators, and how can they be managed?

Freelance machine learning data annotators often encounter challenges such as maintaining data accuracy, handling repetitive tasks, and understanding complex annotation guidelines. Staying organized and regularly reviewing project instructions can help ensure consistency and quality in annotations. Additionally, communicating proactively with project managers and utilizing annotation tools efficiently can help manage workload and clarify uncertainties. Building expertise in different data types (text, image, audio) also allows annotators to diversify their projects and reduce monotony.

What are the most commonly searched types of Machine Learning Data Annotation jobs in Dallas, TX?

The most popular types of Machine Learning Data Annotation jobs in Dallas, TX are:

What are popular job titles related to Freelance Machine Learning Data Annotation jobs in Dallas, TX?

For Freelance Machine Learning Data Annotation jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Freelance Machine Learning Data Annotation jobs in Dallas, TX look for?

The top searched job categories for Freelance Machine Learning Data Annotation jobs in Dallas, TX are:

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Cities near Dallas, TX with the most Freelance Machine Learning Data Annotation job openings:

Freelance Machine Learning Data Annotation jobs near you
Infographic showing various Freelance Machine Learning Data Annotation job openings in Dallas, TX as of June 2026, with employment types broken down into 5% As Needed, 75% Full Time, 10% Part Time, and 10% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $44,993 per year, or $21.6 per hour.

Senior Annotation & Quality Manager

Caterpillar

Irving, TX • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 15 days ago

Caterpillar Inc. rating

7.4

Company rating: 7.4 out of 10

Based on 480 frontline employees who took The Breakroom Quiz

286th of 489 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.
Help Build the Future of Caterpillar.
At Caterpillar, technology always has a purpose, which is to solve our customers' toughest challenges. Through Cat Technology, we are solving problems by building the intelligence layer that connects machines, data, and people to make jobsites safer, more productive, and more sustainable. By combining deep domain expertise in physical systems with software, connectivity, autonomy, and AI, we deliver solutions that work in the real world-on real jobsites, on a global scale.
You'll build and deploy against one of the most unique data foundations-over 1.6 million connected assets generating real-world data daily. These data and platform capabilities are enabling the development of AI models, edge computing architectures, and software systems that scale across fleets, products, and industries. The result will be a new generation of machines that continuously learn, improve, and deliver performance at scale.
Be Part of What's Next in Autonomous Construction Sites
Construction autonomy is one of the most complex challenges in applied AI, and at Caterpillar, advancements in physical AI, simulation, sensing, and edge computing are turning things that once felt impossible-intelligent machines operating in dynamic jobsites-into reality.
Our connected ecosystem brings together massive volumes of high-quality data to create a foundation where engineers like you can build and deploy against.
If this work motivates you, we invite you to join our team. In these roles, you'll work at the intersection of the physical and digital worlds. You'll help design and deliver intelligent systems that enable machines to perceive their environment, make informed decisions, and support safer, more productive operations.
Apply today to build the new era of construction autonomy at Caterpillar.
Role:
We are seeking a Data Annotations & Quality Manager to lead the teams responsible for producing, automating, and validating the datasets that power Physical AI, autonomy, robotics, and machine learning systems.
This leader will oversee three critical functions:
  • Data Annotation - Teams responsible for manual labeling and quality assurance of multimodal sensor data.
  • AI Automation Engineering - Engineers who build and maintain auto-labeling, AI-assisted annotation, and human-in-the-loop systems to improve scalability and efficiency.
  • Data Quality Engineering - Engineers responsible for measuring, monitoring, and enforcing data quality standards across the data lake to ensure datasets remain fit for AI training and production use.

The successful candidate will build and lead a high-performing organization that transforms raw sensor and operational data into trusted, high-quality datasets that enable machine learning, simulation, digital twin, and autonomy initiatives. This role requires a combination of people leadership, operational excellence, data-centric AI expertise, and quality engineering discipline.
What You Will Do
Lead Data Annotation Operations
  • Manage teams responsible for labeling image, video, LiDAR, radar, telemetry, geospatial, and other machine-generated data.
  • Establish scalable annotation processes, standards, and quality controls.
  • Own annotation throughput, quality, cost, and delivery metrics.
  • Drive continuous improvement of annotation workflows, instructions, and quality assurance practices.
  • Partners with AI and software engineering teams align annotation priorities with model development needs.

Lead AI-Powered Annotation Automation
  • Build and lead teams developing auto-labeling, pre-labeling, active learning, and human-in-the-loop annotation solutions.
  • Drive adoption of AI-assisted labeling tools to improve annotation speed and reduce costs.
  • Establish strategies for maximizing automation while maintaining quality and trustworthiness.
  • Define success metrics for automation effectiveness, precision, recall, and reviewer effort reduction.
  • Collaborate with machine learning teams to incorporate model feedback into annotation workflows.

Lead Data Quality Engineering
  • Establish the enterprise data quality strategy for AI training datasets.
  • Define data quality standards, acceptance criteria, and service-level objectives.
  • Implement quality monitoring, anomaly detection, validation rules, and observability capabilities across the data lake.
  • Develop quality scorecards and dashboards that measure dataset health over time.
  • Detect and respond to data degradation, schema drift, annotation drift, missing data, and quality regressions.
  • Ensure training datasets maintain fitness for intended AI use cases.

Deliver Trusted AI Training Data
  • Define data readiness criteria for model training and evaluation.
  • Establish governance for annotation standards, ontologies, labeling guidelines, and dataset versioning.
  • Drive consistency across datasets produced by internal teams and external vendors.
  • Partner with data engineering teams to improve upstream data quality before annotation begins.
  • Partner with machine learning teams to understand model failures and prioritize data improvements.

Build and Develop High-Performing Teams
  • Recruit, develop, and mentor annotation leaders, automation engineers, and data quality engineers.
  • Establish career paths and skills development across all disciplines.
  • Foster a culture focused on quality, innovation, ownership, and continuous improvement.
  • Manage budgets, staffing plans, vendor relationships, and operational priorities.

What You Will Have
Leadership
  • Experience leading technical and operational teams in data, AI, machine learning, analytics, or software engineering environments.
  • Track record of building and scaling high-performing teams.

Data-Centric AI Expertise
  • Strong understanding of how training data impacts machine learning and AI performance.
  • Experience with annotation workflows, ontology management, or dataset development.

Data Quality & Governance
  • Experience establishing data quality standards, monitoring frameworks, and governance processes.
  • Understanding data observability, data validation, and quality measurement techniques.

Software & Automation
  • Experience working with engineering teams building scalable software systems.
  • Familiarity with automation, machine learning workflows, and human-in-the-loop systems.
  • Communication & Influence
  • Ability to communicate effectively with engineering, product, AI, research, and business leaders.
  • Strong stakeholder management and decision-making skills.

Top Candidates Will Have
  • Experience supporting Physical AI, autonomy, robotics, simulation, perception, or digital twin systems.
  • Experience with multimodal data including image, video, LiDAR, radar, GPS, IMU, telemetry, and geospatial data.
  • Experience leading annotation programs involving internal teams, vendors, and AI-assisted labeling systems.
  • Experience building data quality monitoring platforms and observability solutions.
  • Familiarity with active learning, auto-labeling, synthetic data, and human-in-the-loop AI workflows.
  • Experience developing data quality metrics such as completeness, consistency, accuracy, coverage, bias, and drift detection.
  • Experience with cloud-scale data platforms and large data lakes.
  • Experience managing geographically distributed teams.

Additional Details:
  • This position requires the candidate to work full-time at the Irving, Texas office.
  • Domestic relocation assistance is available for this position.
  • Visa sponsorship is available with this position

Summary Pay Range:
$159,120.00 - $258,570.00
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
Posting Dates:
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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