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Full Time Machine Learning Data Annotation Jobs in Austin, TX

AtOrchard LLC

Machine Learning Engineer

Austin, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Develop computer-language subroutines, scripts, and programs that support automated or semi-automated data analysis, annotation, and characterization. * Apply appropriate machine learning and ...

New

Apple

AIML Data Operations - Account & Program Manager

Austin, TX · On-site

$207K - $311K/yr

  • Medical

  • Dental

  • Retirement

Preferred Qualifications Experience with data annotation tools and workflows, and a strong understanding of machine learning concepts and methodologies. Minimum Qualifications 10+ years of experience ...

Apple

AIML Data Operations - Account & Program Manager

Austin, TX · On-site

$207K - $311K/yr

  • Medical

  • Dental

  • Retirement

Preferred Qualifications Experience with data annotation tools and workflows, and a strong understanding of machine learning concepts and methodologies. Minimum Qualifications 10+ years of experience ...

Sourceability

Principal NLP Scientist

Austin, TX · On-site

Strong understanding of data preparation, data quality, labeling workflows, annotation guidelines, and model evaluation metrics * Practical experience with main data analysis and machine learning ...

TalentPros.AI

Staff Machine Learning Engineer

Austin, TX

$120K - $550K/yr

We are looking for visionary Machine Learning Engineers to join our Applied Group, where you'll ... Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they ...

Neuralink

Machine Learning Engineer

Austin, TX · On-site

$199K - $331K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

Additionally, real-world data, such as video feeds, can be encoded into neural data to project ... Base Salary Range: $199,000-$331,000 USD What We Offer: Full-time employees are eligible for the ...

Avride

Machine Learning Engineer

Austin, TX · On-site

The role involves developing and optimizing machine learning models, managing large-scale datasets ... Oversee data collection, preprocessing, and augmentation to maintain high-quality datasets for ...

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

Full Time Machine Learning Data Annotation information

See Austin, TX salary details

$37.2K

$121.7K

$194.8K

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 Austin, TX is $121,659.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,600.00 and $134,800.00 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 the most commonly searched types of Machine Learning Data Annotation jobs in Austin, TX?

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

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

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

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

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

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

Cities near Austin, 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 Austin, TX as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $121,659 per year, or $58.5 per hour.

Machine Learning Engineer

AtOrchard LLC

Austin, TX • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 2 days ago

New

Job description

Description:Machine Learning EngineerRemote with occasional travel to Silver Spring, MD

About @Orchard:

@Orchard is a growing Woman-Owned Small Business and federal prime contractor delivering mission-critical science, data, technology, program management, and workforce solutions. Since 2010, we have built high-performing teams and disciplined delivery systems that help federal agencies launch complex programs, sustain performance, and achieve meaningful mission outcomes.


Position Summary:

@Orchard LLC is seeking an Machine Learning Engineer to support the National Oceanic and Atmospheric Administration (NOAA), Office of Ocean Exploration.


The Machine Learning Engineer will develop and apply machine learning capabilities to help NOAA Ocean Exploration analyze the large volumes of scientific data and video generated during ocean exploration expeditions. Working at the intersection of computer science, marine science, and data analytics, this position will develop software, algorithms, and analytical workflows that help identify scientifically significant characteristics, fauna, shapes, movement, and other features within complex scientific datasets and video streams.


The successful candidate will collaborate with marine scientists, engineers, data specialists, and other technical professionals to improve the efficiency and consistency of scientific data analysis. The role will help reduce manual review time, support annotation and characterization of observations, and create repeatable tools that enable scientists to extract meaningful information from increasingly large ocean exploration datasets.


This position is contingent upon contract award.


Mission Impact:

This position applies emerging AI and machine learning technologies to one of the world's most challenging data environments-ocean exploration. Your work will help NOAA scientists analyze massive volumes of expedition data and video more efficiently, accelerating the identification and characterization of marine life and other scientifically significant observations.


Key Responsibilities:


AI & Machine Learning Development

  • Develop machine learning capabilities for evaluating large volumes of ocean exploration data and streaming video.
  • Design, develop, test, and refine algorithms and software that identify specific characteristics, shapes, movement, fauna, and other features within scientific data and video.
  • Develop computer-language subroutines, scripts, and programs that support automated or semi-automated data analysis, annotation, and characterization.
  • Apply appropriate machine learning and computer vision techniques to improve the efficiency and consistency of scientific data review.
  • Evaluate model performance and refine approaches based on scientific objectives and observed results.


Scientific Data & Video Analysis

  • Work with large scientific datasets and high-volume expedition video to identify patterns and features relevant to ocean exploration.
  • Collaborate with marine scientists to translate scientific questions and observation requirements into computational approaches.
  • Support development of tools that enable scientists to efficiently locate, annotate, classify, and characterize observations.
  • Assist in developing repeatable analytical workflows that can be applied to future expeditions and datasets.
  • Support integration of AI/ML outputs into broader scientific data analysis, annotation, and ocean exploration workflows.


Software Development & Documentation

  • Develop maintainable and reusable code supporting machine learning and data-analysis capabilities.
  • Document software development, algorithms, workflows, model changes, and system updates to support future corrections and enhancements.
  • Test and troubleshoot applications and analytical workflows to ensure reliable performance.
  • Recommend improvements to software, analytical methods, and machine learning workflows.
  • Support software corrections and updates as required.


Scientific Collaboration

  • Collaborate with marine scientists, GIS specialists, web developers, engineers, and other technical professionals.
  • Participate in technical discussions, scientific meetings, and project planning activities.
  • Translate technical machine learning concepts into understandable information for scientific and program stakeholders.
  • Support technical reports, presentations, demonstrations, and other program deliverables.


Operational Support

  • Support response to urgent software or analytical issues affecting supported capabilities, including occasional work outside normal business hours when required
  • Support troubleshooting and resolution of issues affecting machine learning applications and associated web or data capabilities.
Requirements:
  • Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Marine Science, Oceanography, or related discipline. Master's degree preferred.
  • Experience developing or applying machine learning solutions for data analysis, computer vision, video analysis, or related applications.
  • Programming experience in Python or another modern programming language.
  • Experience working with large datasets and developing repeatable data-analysis workflows.
  • Understanding of machine learning concepts, model development, evaluation, and optimization.
  • Strong analytical and problem-solving skills.
  • Ability to collaborate effectively with scientists and technical professionals from different disciplines.
  • Excellent written and verbal communication skills.
  • Proficiency with Microsoft Office 365, Google Workspace, and Adobe Acrobat.
  • Occasional domestic travel may be required to support scientific meetings, workshops, planning sessions, training activities, or other program requirements consistent with contract needs.
  • Must be eligible to obtain and maintain a Department of Commerce / NOAA federal background investigation and suitability determination and be authorized to work in the United States without employer sponsorship.

Preferred Skills and Experience:

  • Experience applying AI or machine learning to scientific, environmental, marine, or oceanographic datasets is preferred.
  • Experience with computer vision, image recognition, object detection, video analytics, or image classification.
  • Experience working with high-volume video or streaming data.
  • Experience with deep learning frameworks such as PyTorch or TensorFlow.
  • Experience with scientific Python libraries and data-analysis tools.
  • Experience supporting NOAA, other federal agencies, academic research organizations, or marine science programs.
  • Familiarity with marine organisms, oceanographic data, or scientific expedition environments.


Technical Skills:

  • Python
  • Data Analysis
  • Large-Scale Data Processing
  • Algorithm Development
  • Software Testing & Troubleshooting
  • Scientific Data Workflows


Compensation: The anticipated salary range for this position depends on the candidate's qualifications, relevant scientific experience, education, and overall experience supporting similar federal programs.


What We Offer:

Competitive base salary with opportunities for advancement, career growth and professional development, work-life balance, comprehensive benefits including health, dental, vision, life insurance, 401(k), generous PTO, and paid federal holidays.


If you are passionate about artificial intelligence, machine learning, and applying innovative technology to ocean exploration, we encourage you to join our team and help transform massive volumes of scientific data into discoveries that advance our understanding of the world's oceans.


@Orchard is an equal opportunity employer. We encourage all qualified candidates to apply, regardless of race, gender, age, disability, or other protected characteristics.


To learn more about our other exciting opportunities, visit our Jobs Page at www.atorchard.com.