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Full Time Machine Learning Data Annotation Jobs in Houston, TX

Weatherford

Data Scientist - Wireline

Houston, TX

In this role, you will apply advanced data analytics, machine learning, and scientific modeling to solve complex problems related to downhole tools, signal processing, and formation evaluation. The ...

Forum Energy Services, Inc.

AI Architect

Houston, TX

$60.75 - $78.25/hr

The ideal candidate will possess a hybrid skill set spanning machine learning, data engineering, and software development, with a passion for building scalable AI systems and a strong foundation in ...

Vitol

Software Engineer in Data Science

Houston, TX · On-site

$109K - $131K/yr

Vitol is the world's largest independent energy and commodities trading company, and they are seeking an experienced Software Engineer to join their global data science and machine learning team. The ...

Forum Energy Technologies

AI Architect

Houston, TX · On-site

$60.75 - $78.25/hr

The ideal candidate will possess a hybrid skill set spanning machine learning, data engineering, and software development, with a passion for building scalable AI systems and a strong foundation in ...

NAVA Software Solutions

Principal Data Engineer

Houston, TX · On-site

$106K - $127K/yr

Houston, TX - 4 days/week onsite Duration: Full time / Direct Hire The Principal Data Engineer ... Collaborate closely with business analysts, data scientists, machine learning engineers, and ...

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

Full Time Machine Learning Data Annotation information

See Houston, TX salary details

$35.8K

$117.2K

$187.7K

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

As of Aug 14, 2026, the average yearly pay for full time machine learning data annotation in Houston, TX is $117,212.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,100.00 and $129,900.00 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 is a full time machine learning data annotation job?

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 popular job titles related to Full Time Machine Learning Data Annotation jobs in Houston, TX?

For Full Time Machine Learning Data Annotation jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching Full Time Machine Learning Data Annotation jobs in Houston, TX look for?

The top searched job categories for Full Time Machine Learning Data Annotation jobs in Houston, TX are:

What cities near Houston, TX are hiring for Full Time Machine Learning Data Annotation jobs?

Cities near Houston, 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 Houston, TX as of July 2026, with employment types broken down into 19% Full Time, 8% Part Time, 67% Contract, and 6% Nights. Highlights an 4% Physical, and 96% Remote job distribution, with an average salary of $117,212 per year, or $56.4 per hour.

Data Analyst / Data Scientist (2-4 years)

Hudson Manpower

Houston, TX • On-site

$50K - $75K/yr

Full-time

Posted 21 days ago

Job description


We are looking for early-career Data Analytics / Data Science professionals who are passionate about working with data and deriving meaningful insights. Candidates with internship experience, academic projects, or personal projects are highly encouraged to apply.
This role is ideal for candidates looking to build a strong foundation in data analytics and data science while working on real-world business problems.
Experience: 6 Months - 2/3/4 Years
Employment Type: Full Time W2 Only
Work Authorization: US Citizens Only
Location: Open to Relocation Anywhere in the United States
Key Responsibilities:
  • Collect, clean, and analyze structured and unstructured data
  • Develop reports, dashboards, and visualizations to support decision-making
  • Perform exploratory data analysis (EDA) and identify trends and patterns
  • Assist in building predictive models and basic machine learning solutions
  • Work closely with business and technical teams to understand data requirements
  • Document findings and present insights to stakeholders

Required Skills:
  • Strong understanding of SQL
  • Proficiency in Python or R
  • Knowledge of Excel and data manipulation techniques
  • Familiarity with data visualization tools (Tableau, Power BI, or similar)
  • Basic understanding of statistics and data modeling concepts

Nice to Have:
  • Exposure to Machine Learning concepts
  • Experience with cloud platforms (AWS, Azure, or GCP - basic level)
  • Hands-on experience through internships, academic projects, or personal projects
  • Knowledge of Pandas, NumPy, Matplotlib/Seaborn, or Scikit-learn

Eligibility Criteria:
  • US Citizens only
  • 6 months to 2 years of experience (internships & projects count)
  • Must be willing to relocate anywhere in the United States
  • Open to early-career professionals and fresh graduates with strong project work

Apply