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Full Time Machine Learning Data Annotation Jobs in Dallas, TX

Resolve Tech Solutions

Senior ML Engineer

Addison, TX · On-site

$101K - $138K/yr

Develop machine learning models and algorithms to address business needs. Collaborate with data scientists and software engineers to design and implement scalable and efficient solutions. Clean ...

Resolve Tech Solutions

Senior ML Engineer

Addison, TX · On-site

$101K - $138K/yr

Responsibilities: • Develop machine learning models and algorithms to address business needs. • Collaborate with data scientists and software engineers to design and implement scalable and ...

Capital One

Lead Machine Learning Engineer

Plano, TX

$98K - $129K/yr

Ensure all AI/ML applications strictly adhere to robust data privacy standards, regulatory postures ... The minimum and maximum full-time annual salaries for this role are listed below, by location.

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

Ensure all AI/ML applications strictly adhere to robust data privacy standards, regulatory postures ... The minimum and maximum full-time annual salaries for this role are listed below, by location.

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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 Jul 18, 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 July 2026, with employment types broken down into 2% Locum Tenens, 34% Full Time, 14% Part Time, 15% Contract, 34% Nights, and 1% Summer. Highlights an 34% Physical, and 66% Remote job distribution, with an average salary of $121,417 per year, or $58.4 per hour.
Sr. Principal Data Scientist / Machine Learning Engineer

Sr. Principal Data Scientist / Machine Learning Engineer

Ascentt

Plano, TX • On-site

Full-time

Re-posted 13 days ago

Job description

Job Summary:
Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We are seeking a skilled Sr. Principal Data Scientist / Machine Learning Engineer to lead high-impact AI/ML projects, leveraging deep data science expertise to drive business value and client satisfaction.
Responsibilities:
• Serve as a primary technical expert and thought leader in Data Science and Machine Learning.
• Define and drive the technical strategy for AI/ML initiatives, identifying high-value opportunities for optimization, predictive analytics, and process improvement across diverse use cases.
• Architect and oversee the development of robust, scalable, and production-ready DS/ML models and solutions.
• Stay at the forefront of the latest advancements in DS/ML, especially those applicable to various industries and large-scale data problems.
• Lead end-to-end DS/ML projects, including requirements gathering, data exploration, model development, validation, deployment, and monitoring.
• Define project scope, timelines, and deliverables, ensuring successful execution within budget and schedule constraints.
• Mentor and guide junior and mid-level data scientists and ML engineers, fostering a culture of technical excellence and continuous learning.
• Drive MLOps best practices for reliable and efficient model deployment and lifecycle management.
• Act as a trusted advisor to clients and internal stakeholders, understanding their business challenges and translating them into solvable DS/ML problems.
• Effectively communicate complex analytical findings, model performance, and business recommendations to both technical and non-technical audiences.
• Manage client expectations, present progress reports, and ensure stakeholder satisfaction.
• Facilitate workshops and discovery sessions to identify new opportunities for AI/ML adoption.
• Lead the identification, prioritization, and execution of complex AI/ML use cases that drive significant business impact.
• Apply deep analytical skills to dissect complex problems, derive actionable insights from data, and design innovative solutions.
• Develop and implement models for:
• Predictive Analytics: Forecasting, risk assessment, and anomaly detection.
• Optimization: Improving efficiency, resource allocation, and decision-making.
• Pattern Recognition: Identifying trends, segments, and relationships within large datasets.
• Automation: Leveraging ML for intelligent process automation and enhanced operational efficiency.
Qualifications:
Required:
• Master's or Ph.D. in Data Science, Machine Learning, Computer Science, Engineering, Operations Research, Statistics, or a related quantitative field.
• 8+ years of progressive experience in Data Science and Machine Learning roles, with at least 3-5 years in a leadership or principal-level capacity.
• Demonstrated experience leading multiple end-to-end DS/ML projects successfully from concept to production.
• Proven track record of managing client interactions, presenting technical solutions, and influencing strategic decisions.
• Expertise in Python programming (NumPy, Pandas, Scikit-learn, Keras/TensorFlow/PyTorch).
• Strong understanding of statistical modeling, experimental design, and hypothesis testing.
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps principles.
• Excellent communication, interpersonal, and presentation skills.
Preferred:
• Experience with real-time data processing and streaming analytics.
• Knowledge of various industry verticals and their unique data challenges (e.g., finance, healthcare, retail, logistics, manufacturing).
• Experience with large-scale data architectures (e.g., data lakes, data warehouses, distributed computing).
• Publications or presentations in relevant fields.
Company:
Ascentt is an AI, ML and Data Science solutions provider serving enterprise customers. Founded in 2007, the company is headquartered in Plano, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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