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Full Time Machine Learning Data Annotation Jobs in Dallas, TX

Vogo

Data Scientist

Dallas, TX · On-site +1

This role will own the Machine Learning models that drive our business from development to ... This role will report directly to the COO. This is a full-time hybrid position, based in Dallas.

TECHOAUTH SOLUTIONS LLC

Senior Data Engineer

Fort Worth, TX · On-site +1

$70K - $120K/yr

Experience working with AI or machine learning data platforms Work Environment * Hybrid work model (Fort Worth office + remote work) * Standard business hours with occasional on-call support for data ...

Vanguard

Manager, Machine Learning Engineer

Dallas, TX

$101K - $133K/yr

Leads a team of Machine Learning Engineers responsible for designing, building, deploying, and ... Partners closely with Product, Data Science, Architecture, and Technology teams to deliver ...

Purple Drive Technologies

Data Scientist

Plano, TX · On-site

Data Scientist Location: San Antonio, TX / Plano, TX (Onsite) Employment Type: Contract Experience ... This role requires strong expertise in Python, R, SQL, statistical modeling, and machine learning ...

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All JobsMachine Learning Data Annotation JobsFull Time Machine Learning Data Annotation JobsFull Time Machine Learning Data Annotation Jobs in Dallas, TX

Full Time Machine Learning Data Annotation information

See Dallas, TX salary details

$37.1K

$121.4K

$194.4K

How much do full time machine learning data annotation jobs pay per year?

As of Jun 9, 2026, the average yearly pay for full time machine learning data annotation in Dallas, TX is $121,417.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,400.00 and $134,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Full Time Machine Learning Data Annotation Specialist, and why are they important?

To thrive as a Full Time Machine Learning Data Annotation Specialist, you need strong attention to detail, basic data literacy, and familiarity with data labeling concepts, often supported by a high school diploma or equivalent. Proficiency in specialized annotation platforms, spreadsheet tools, and sometimes knowledge of Python or labeling frameworks is typically required. Reliability, patience, and effective communication are valuable soft skills for ensuring accuracy and collaborating with team members. These skills and qualities are crucial because they directly impact the quality of training data, which is essential for developing effective machine learning models.

What are Full Time Machine Learning Data Annotation jobs?

Full time machine learning data annotation jobs involve labeling, tagging, or categorizing data such as images, text, audio, or video to help train machine learning models. Data annotators play a crucial role in ensuring that AI systems learn from high-quality, accurately labeled datasets. These positions often require attention to detail, consistency, and sometimes familiarity with the subject matter or specialized tools. Full-time roles may be remote or onsite and can span industries like autonomous vehicles, healthcare, retail, and more.

What are some common challenges faced by machine learning data annotators, and how are these typically addressed within a team?

Machine learning data annotators often encounter challenges such as maintaining consistency in labeling, handling ambiguous data, and meeting tight deadlines for large datasets. Teams usually address these by establishing clear annotation guidelines, conducting regular training sessions, and implementing quality assurance processes like peer reviews and spot checks. Collaboration with data scientists and project managers is also common, ensuring that annotators can ask questions and clarify uncertainties, leading to higher-quality labeled data and a supportive work environment.

What is the difference between Full Time Machine Learning Data Annotation vs Data Labeling Specialist?

AspectFull Time Machine Learning Data AnnotationData Labeling Specialist
CredentialsHigh school diploma or equivalent; some roles prefer technical certificationsHigh school diploma or equivalent; training often provided on the job
Work EnvironmentOffice or remote; collaborative with data science teamsRemote or office; focused on labeling tasks
Industry UsageUsed across AI/ML companies, tech firms, and startupsCommon in AI/ML, data services, and outsourcing companies
Job FocusCreating labeled datasets for machine learning modelsAnnotating data such as images, videos, or text for AI training

Full Time Machine Learning Data Annotation involves creating high-quality labeled datasets for AI models, often requiring technical understanding. Data Labeling Specialists focus on annotating data accurately, typically with less emphasis on technical skills. Both roles are essential in AI development but differ mainly in scope and technical complexity.

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 Full Time Machine Learning Data Annotation jobs in Dallas, TX? For Full Time Machine Learning Data Annotation jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Full Time Machine Learning Data Annotation jobs in Dallas, TX look for? The top searched job categories for Full Time Machine Learning Data Annotation jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Full Time Machine Learning Data Annotation jobs? Cities near Dallas, TX with the most Full Time Machine Learning Data Annotation job openings:
Full Time Machine Learning Data Annotation jobs near you
Infographic showing various Full Time Machine Learning Data Annotation job openings in Dallas, TX as of May 2026, with employment types broken down into 1% As Needed, 73% Full Time, 20% Part Time, and 6% Contract. Highlights an 46% Physical, 1% Hybrid, and 53% Remote job distribution, with an average salary of $121,417 per year, or $58.4 per hour.

Data Scientist

Vogo

Dallas, TX • On-site, Remote

Full-time

Posted 24 days ago

Job description

About Vogo
Vogo is a global travel platform that brings all types of accommodations into one place, making it easy for travelers to find the perfect stay.
 
From downtown hotels and luxury resorts to private vacation rentals and remote cabins, Vogo offers the widest selection of accommodations worldwide. Vogo's proprietary technology then scans billions of data points to surface the best deals across millions of properties, streamlining discovery, and booking for every traveler.
 
Since launching out of Wilbur Labs in 2018, Vogo has rapidly become one of the most trusted travel platforms globally, surpassing $1 billion in gross bookings in just two years. Vogo is headquartered in Dallas and led by a team of travel industry veterans.
 
About this Role
Vogo is seeking a hands-on, data-driven Data Scientist to support the next stage of growth. This role will own the Machine Learning models that drive our business from development to deployment. Key responsibilities include improving on sort and search models to help travelers find their perfect accommodation quickly and efficiently, refining predictive and classification models to estimate cancellations and financial outcomes, and developing new models to choose the perfect images and reviews to show to our customers. Your work will directly improve both customer experience and business performance. 
 
The ideal candidate combines top-notch model development and tuning skills with a startup mindset: pragmatic, ownership-driven, and excited to make a measurable impact. This is a strategic, execution-focused role for someone who can drive Machine Learning initiatives end-to-end and deliver results independently.
 
Success in this role requires more than strong technical skills. Improved models and engineering must translate into better financial and customer outcomes, so strong business judgment is essential. Identifying the right problems to solve is just as important as the modeling itself. This role is positioned to have a direct and meaningful impact on the business. 
 
This role will report directly to the COO. This is a full-time hybrid position, based in Dallas. 
Roles and Responsibilities:
  • Model Development: Design, develop, and implement machine learning models to drive VacationRenter’s sort and search functions, create classification models to predict reservation cancellations, and build predictive models to support pricing strategies
  • Data Analysis & Feature Engineering: Leverage your business acumen and deep understanding of travel shopping behaviors to identify, engineer, and prioritize the most impactful features that drive model performance
  • Production Deployment: Collaborate with engineering teams to deploy machine learning models into production, ensuring they perform reliably, scale effectively, and maintain high-quality results
  • Experimentation & A/B Testing: Design and run controlled experiments to measure and validate the effectiveness and impact of machine learning models
  • Reporting & Visualization: Develop clear and insightful reports and interactive dashboards to effectively communicate model findings and performance metrics to both technical and non-technical stakeholders
  • Research & Innovation: Continuously explore and apply the latest advancements in machine learning, AI, and data science to enhance our modeling capabilities and data infrastructure
Minimum Qualifications:
  • 5+ years of professional experience in a Data Scientist or Machine Learning Engineer role,
  • Expert-level proficiency in Python, including key machine learning libraries
  • Solid understanding of statistical modeling, experimental design, and data mining techniques
  • Demonstrated experience owning the full modeling lifecycle, including ETL, data cleansing, feature engineering, model development, deployment, and ongoing maintenance
  • Experience with SQL and working with large datasets in a cloud environment, particularly GCP, but demonstrated expertise in other platforms can suffice
  • Strong communication skills, with the ability to explain complex technical concepts to a diverse audience
Preferred Qualifications and Prior Experience:
  • Experience  developing machine learning models within a GCP environment
  • Familiarity with MLOps practices and tools for deployment, maintenance, and ongoing improvement of models
  • Experience in the Travel or Financial Services industry
Benefits & Perks:
  • Competitive salary + equity
  • Top-tier laptop provided
  • 100% company-paid health benefits for base plan coverage, with the option to upgrade to higher-tier plans
  • 401(k) with company match
  • Unlimited, guilt-free vacation days
  • Annual wellness stipend (gym + other wellness activities)
  • Monthly house cleaning stipend
  • Annual travel allowance
  • Monthly cell phone & internet usage stipend
  • Charity donation company match
  • Employee referral bonus
  • Team offsites/activities!

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.