Explore 3 machine learning data annotator jobs from 3 hiring companies in United States. Filter by remote, salary, experience, and company, then open any listing to apply.

machine-learning-data-annotator

Machine Learning Data Annotator

California

Texas

New York

Florida

Illinois

Pennsylvania

Ohio

North Carolina

Michigan

Georgia

New Jersey

Virginia

Massachusetts

Washington

Indiana

Tennessee

Arizona

Missouri

Maryland

Wisconsin

Minnesota

Colorado

Alabama

Louisiana

South Carolina

Kentucky

Oregon

Oklahoma

Connecticut

Iowa

Mississippi

Arkansas

Kansas

Utah

Nevada

New Mexico

West Virginia

Nebraska

Idaho

Maine

New Hampshire

Hawaii

Rhode Island

Montana

Delaware

South Dakota

Alaska

North Dakota

Vermont

District of Columbia

Wyoming

Machine Learning Data Annotator Jobs

Apple

Bot Auto

Correlation One

Hybrid

Onsite

Remote

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or experience we deliver is the result of us making each other’s ideas stronger. The diversity of our people and their thinking inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something — you’ll add something.<h3>Description</h3>The Special Projects team at Apple is developing novel user-facing conversational features that leverage the multimodal capabilities of state-of-the-art foundation models. As part of this process, we generate real-world and simulated data, gather human data annotations, analyze the results, and use them to build and evaluate Large Language Model judges. We are looking for a skilled Data Scientist to join our Machine Learning Evaluations teams. This person will work closely with ML Engineers to manage and analyze our human and automated data annotation processes, and to develop, test, and refine LLM judges for generative AI model evaluation. A successful candidate is experienced in survey design, data annotation, LLM prompt engineering and prompt optimization, and has strong statistical analysis skills.<h3>Minimum Qualifications</h3><ul><li>BA or Master’s degree in Data Science, Statistics, or a quantitative social science field</li><li>2+ years of hands-on experience working in survey design and human data annotation</li><li>Proficiency in Python</li><li>Excellent communication skills</li></ul><h3>Preferred Qualifications</h3><ul><li>PhD in Data Science, Statistics, or a quantitative social science field</li><li>Hands-on industry experience with product-focused statistical analysis</li><li>Experience working with large-scale multimodal data and data-annotation pipelines</li><li>Experience with LLM prompt engineering &amp; prompt optimization</li><li>Experience with LLM auto-judges for generative AI model evaluation</li><li>A track record of publications or technical presentations in Data Science or a related field</li><li>Excellent at cross-functional collaboration</li></ul>

Data Scientist - Survey Design, Data Annotation, and Machine Learning Evaluation

Data Scientist

BA or MS in Data Science/Statistics; 2+ years in survey design and human data annotation; Python proficiency; strong communication.

Correlation One develops workforce skills for the AI economy
Enterprises and governments work with us to develop talent and close critical data, digital, and technology skills gaps. Our global programs, including training programs and data competitions, also empower underrepresented communities and accelerate careers.
Our mission is to create equal access to the data-driven jobs of the future. We partner with top employers and government organizations to make that a reality, including Amazon, Coca-Cola, Johnson &amp; Johnson, the U.S. State Department, and the U.S. Department of Defense.
Our skills training programs are 100% free for learners and are delivered virtually by industry experts to minimize traditional barriers to career advancement. We take pride in fostering supportive, human-led, group learning environments that build technical proficiency and confidence in participants.
Join us and let's shape the AI Economy together!
Your impact&nbsp;
Teaching Assistants (TAs) play a critical role in supporting ~25-30 Learners (as part of a larger class) in Correlation One’s virtual training programs. During that time, TAs will be expected to provide both synchronous and asynchronous support to Learners in German, ensuring their learning, comprehension, and retention of program content. This is a part time, contract position.&nbsp;
Program Specific Information: Please note these dates and times are tentative and subject to change. If you aren't available for these dates/times, we still encourage you to apply.
<ul>
<li>Dates: May 4, 2026 – September 23, 2026</li>
<li>Frequency: Every Monday &amp; Wednesday</li>
<li>Time: 1:00 PM – 3:00 PM EST / 7:00 PM – 9:00 PM CEST</li>
</ul>
A day in the life&nbsp;
Expectations during live (synchronous) sessions:
<ul>
<li>Attend and proactively engage in the mandatory Pre-Program TA Onboarding. Dates and times will be announced.&nbsp;</li>
<li>Monitor appropriate Slack channels (#c1-TA, #live-chat, #extra-help, and other relevant channels) for Learner questions and answer them promptly.&nbsp;</li>
<li>Check-in with Learners after each live session by asking how they’re feeling about the content, if they have any questions, or if there is anything that they need further clarity.</li>
<li>Facilitate breakout rooms during lecture time, when applicable.</li>
<li>Assist in keeping the session progressing should the Lead Instructor experience technical difficulty or is otherwise unable to deliver the lecture.</li>
</ul>
Expectations during days of no live sessions:&nbsp;
<ul>
<li>Monitor appropriate Slack channels for Learner questions and answer them within 24 hours.&nbsp;</li>
<li>Foster discussion by posing questions of your own and sharing relevant links in the #resources channel or in other appropriate Slack channels.</li>
<li>Use the #c1-TA channel to share any important information during a lecture that needs the attention of Correlation One staff or fellow Expert Network staff.&nbsp;</li>
<li>Review content materials (including lab, projects, extended cases, etc..) for the next lecture to ensure you are prepared to answer Learner questions.</li>
<li>Hold up to six (6) Individual Office Hours via Zoom with Learners in the program so they can ask any additional questions or get support as necessary.</li>
<li>Grade Learner submissions of exercises and projects within seven (7) days of submission.&nbsp;</li>
<li>Support continuous program improvement by providing thoughtful feedback to Correlation One team via Weekly Write Ups.</li>
<li>Submit weekly write-ups summarizing the week’s accomplishments and challenges and provide insights on each Learner.&nbsp;</li>
<li>Attend and participate in the weekly staff meeting with Correlation One team and other Expert Network staff.&nbsp;</li>
<li>Attend all scheduled meetings with your camera on, ensuring active engagement and professional presence.&nbsp;</li>
</ul>
Your expertise&nbsp;
<ul>
<li>Bilingual Communication: Demonstrate professional fluency in both German and English to provide technical support and feedback to learners in their primary language.</li>
<li>Technical Proficiency: Possess a solid foundational understanding of machine learning principles, generative AI, and the data annotation lifecycle.</li>
<li>Professional Data Annotation Background: Have at least 1–2 years of professional working experience performing or leading labeling/QA workflows across text, image/video, and speech/audio, with strong consistency and guideline adherence.</li>
<ul>
<li>Data Handling: Previous experience or familiarity with data annotation, labeling, or quality control processes is highly preferred.</li>
</ul>
<li>AWS Certification: Hold an active AWS Certified AI Practitioner certification to effectively support students through the program's technical and certification tracks.</li>
<li>Written Precision: Exhibit strong writing skills to guide learners in developing high-quality, structured rationales for AI data labeling tasks.</li>
<li>Quality Assurance Aptitude: Ability to use spreadsheet tools (like Excel or Google Sheets) to track learner progress and identify common technical errors in data labeling exercises.</li>
<li>Learner Support: Proven experience providing academic or technical support to learners, either as a teaching assistant, tutor, or peer mentor in a virtual setting.</li>
<li>Virtual Collaboration: Experience working with remote teams and using digital communication tools like Slack and Zoom to facilitate group learning.</li>
<li>Feedback Delivery: Demonstrated ability to provide constructive, empathetic, and timely feedback on technical labeling assignments and projects.</li>
</ul>
Where you are
<ul>
<li>This role is remote and can be performed anywhere that is compatible with the EST time zone.&nbsp;</li>
</ul>
Correlation One’s Commitment&nbsp;
Correlation One is proud to be an Equal Opportunity Employer and is committed to providing equal opportunity for all employees and applicants. Correlation One provides a work environment free of discrimination and harassment. Employment decisions at Correlation One are based solely on business needs, job requirements and individual qualifications, without regard to race, color, religion or belief, national, social or ethnic origin, sex (including pregnancy), age, sexual orientation, gender identity and/or expression, marital, civil union or domestic partnership status, past or present military service, or any other status protected by the laws or regulations in the locations where we operate. &nbsp;We encourage applicants to bring their unique skills, experiences, and outlook to our work environment.&nbsp;
Correlation One is committed to the full inclusion of all qualified individuals. In keeping with our commitment, Correlation One strives to provide reasonable accommodations for persons with disabilities to enable them to access the hiring process. If you need an accommodation to access the job application or interview process, please contact <a href="mailto:candidates@correlation-one.com">candidates@correlation-one.com</a>.
#priority

Teaching Assistant: Machine Learning Data Associate

Teaching Assistant

Part-time contract TA role supporting German learners; bilingual in German and English; strong data annotation background; AWS AI Practitioner certification; proficient with Slack/Zoom; remote.

<h2>Company Introduction</h2>
At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a start-up and the wisdom of seasoned experts, Bot Auto boasts a team that has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create miracles and propel the future of transportation. Join us and transform your dreams into reality.
We are seeking a highly skilled and motivated Software Engineer to design, develop, and scale our machine learning annotation, evaluation, and training infrastructure. This role is central to the quality and velocity of our perception and ML models — from curating and managing high-quality annotated datasets, to building robust evaluation pipelines that drive continuous model improvement. The ideal candidate combines strong systems engineering skills with a deep understanding of ML Workflows/Ops and large-scale data infrastructure.
<h2>Key Responsibilities</h2>
Machine Learning &amp; Deep Learning Infrastructure
<ul>
<li>Evaluation Platform — Architect and own a scalable, end-to-end model evaluation platform for perception and prediction models central to autonomous driving. Define metrics, design for scale, and make results actionable for researchers.</li>
<li>Training Infrastructure — Partner with research scientists to optimize and scale distributed training workflows. Integrate experiment tracking and reproducibility into the model lifecycle from day one.</li>
<li>Dataset &amp; Feature Store — Design and maintain a versioned, high-quality training data store that accelerates model development and supports rapid iteration.</li>
<li>ML Pipelines — Build automated pipelines spanning data preparation, model training, validation, and deployment — enabling fast experimentation and reproducible outcomes.</li>
<li>Annotation Platform — Contribute to tooling and infrastructure that powers high-throughput, high-accuracy data annotation at scale.</li>
<li>MLOps — Develop production ML services that treat models as products — with reliability, observability, and continuous improvement built in.</li>
</ul>
Data Infrastructure
<ul>
<li>Maintain and evolve a robust data storage and access layer (S3 data lake, Delta Lake) underpinning annotation, evaluation, and training workflows.</li>
<li>Build scalable, reliable data collection pipelines supporting diverse vehicle dispatch missions.</li>
<li>Develop foundational services and packages that provide clean, performant access to autonomous driving data across the stack.</li>
</ul>
<h2>Qualifications</h2>
Required:
<ul>
<li>Educational Background: Bachelor's or Master's in Computer Science, or equivalent practical experience.</li>
<li>Strong Programming Skills: Strong proficiency in Python; working knowledge of C++</li>
<li>ML/DL Infrastructure Experience — Demonstrated hands-on experience building or scaling at least one of the following in a production environment:</li>
<ul>
<li>Evaluation platforms — automated model benchmarking, metric computation, and regression tracking across model versions.</li>
<li>Training infrastructure — distributed training pipelines, experiment tracking, and model lifecycle management (e.g. W&amp;B, MLflow, ClearML).</li>
<li>Dataset curation &amp; feature stores — versioned dataset management, data lineage, and tooling for high-quality training data at scale.</li>
<li>Annotation platforms — tooling or pipelines that support high-throughput, high-accuracy labeling workflows.</li>
</ul>
<li>Distributed Systems — Strong experience with distributed computing and container orchestration — Kubernetes, Spark, or comparable frameworks.</li>
<li>Ability to operate independently: scope ambiguous problems, make sound architecture decisions, and drive them to completion.</li>
</ul>
Preferred:
<ul>
<li>C++ experience in performance-sensitive or safety-critical applications</li>
<li>Full-stack service development experience.</li>
<li>Prior work in autonomous driving or robotics.</li>
</ul>

Software Engineer - Machine Learning Infrastructure 

Software Engineer

Design and scale ML annotation, evaluation, and training infrastructure; strong Python, ML/DL, distributed systems, and data pipelines.

Machine Learning Data Annotator Jobs in United States | HiringCafe: every job on earth

Machine Learning Data Annotator Jobs in United States

Machine Learning Data Annotator Jobs market signals in United States

Companies appearing in this market

Work location mix in visible results

Related browse hubs