Teaching Assistant: Machine Learning Data Associate

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.

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.

• Dates: May 4, 2026 - September 23, 2026
• Frequency: Every Monday & Wednesday
• Time: 1:00 PM - 3:00 PM EST / 7:00 PM - 9:00 PM CEST

A day in the life

Expectations during live (synchronous) sessions:

• Attend and proactively engage in the mandatory Pre-Program TA Onboarding. Dates and times will be announced.
• Monitor appropriate Slack channels (#c1-TA, #live-chat, #extra-help, and other relevant channels) for Learner questions and answer them promptly.
• 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.
• Facilitate breakout rooms during lecture time, when applicable.
• Assist in keeping the session progressing should the Lead Instructor experience technical difficulty or is otherwise unable to deliver the lecture.

Expectations during days of no live sessions:

• Monitor appropriate Slack channels for Learner questions and answer them within 24 hours.
• Foster discussion by posing questions of your own and sharing relevant links in the #resources channel or in other appropriate Slack channels.
• 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.
• Review content materials (including lab, projects, extended cases, etc..) for the next lecture to ensure you are prepared to answer Learner questions.
• 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.
• Grade Learner submissions of exercises and projects within seven (7) days of submission.
• Support continuous program improvement by providing thoughtful feedback to Correlation One team via Weekly Write Ups.
• Submit weekly write-ups summarizing the week's accomplishments and challenges and provide insights on each Learner.
• Attend and participate in the weekly staff meeting with Correlation One team and other Expert Network staff.
• Attend all scheduled meetings with your camera on, ensuring active engagement and professional presence.

Do you have experience in Writing skills?, * Bilingual Communication: Demonstrate professional fluency in both German and English to provide technical support and feedback to learners in their primary language.

• Technical Proficiency: Possess a solid foundational understanding of machine learning principles, generative AI, and the data annotation lifecycle.
• 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.

• Data Handling: Previous experience or familiarity with data annotation, labeling, or quality control processes is highly preferred.

• AWS Certification: Hold an active AWS Certified AI Practitioner certification to effectively support students through the program's technical and certification tracks.
• Written Precision: Exhibit strong writing skills to guide learners in developing high-quality, structured rationales for AI data labeling tasks.
• 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.
• Learner Support: Proven experience providing academic or technical support to learners, either as a teaching assistant, tutor, or peer mentor in a virtual setting.
• Virtual Collaboration: Experience working with remote teams and using digital communication tools like Slack and Zoom to facilitate group learning.
• Feedback Delivery: Demonstrated ability to provide constructive, empathetic, and timely feedback on technical labeling assignments and projects.