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Full Time Machine Learning Data Annotation Jobs in Dallas, TX

Bespoke Labs

Machine Learning Engineer

Mckinney, TX · On-site

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Bespoke Labs

Machine Learning Engineer

Arlington, TX · On-site

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Bespoke Labs

Machine Learning Engineer

Dallas, TX · On-site

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

TECHOAUTH SOLUTIONS LLC

Senior Data Engineer

Fort Worth, TX · Hybrid

$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 ...

TECHOAUTH SOLUTIONS LLC

Senior Data Engineer

Fort Worth, TX · Hybrid

$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 ...

TECHOAUTH SOLUTIONS LLC

Senior Data Engineer

Fort Worth, TX · On-site

$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 ...

Equinix

AI/Machine Learning Engineer

Dallas, TX · Remote

Implement data and model pipelines integrating structured and unstructured data sources * Work ... full-time position determined by role, level, and location. The pay range shown is based on our ...

New

Equinix, Inc.

AI/Machine Learning Engineer

Dallas, TX · On-site

Implement data and model pipelines integrating structured and unstructured data sources * Work ... full-time position determined by role, level, and location. The pay range shown is based on our ...

New

Vangard, Inc.

Data Engineer, Specialist

Dallas, TX · On-site

$113K - $136K/yr

Machine Learning * Data Governance * Minimum of five years data analytics, programming, database administration, or data management experience. * Undergraduate degree or equivalent combination of ...

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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 17, 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.

Machine Learning Engineer

Bespoke Labs

Mckinney, TX • On-site

Full-time

Posted 8 hours ago

Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination

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