Lead Instructor: Machine Learning Data Associate

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CORRELATION ONE Correlation One is the largest provider of AI and data workforce development programs globally, having trained over 500,000 professionals across 11 countries. As the largest training provider for Amazon Career Choice, and a growing partner to state governments building registered apprenticeship programs, Correlation One sits at the intersection of employer talent needs and scalable workforce training. We work with Fortune 500 enterprises, federal and state government agencies, and leading employers to close skills gaps in AI, data analytics, cybersecurity, and operations leadership. Our programs produce job-ready graduates who are prepared to contribute from day one. Job Summary: Lead Instructors at Correlation One are responsible for delivering high-quality, live, virtual instruction and partnering with company personnel to drive exceptional learning outcomes. Their main focus as educators is to conduct large synchronous online lectures on technical content, training anywhere from 100 to 8,000+ diverse learners at a time, depending on the program. This role involves preparing and leading virtual classroom sessions, collaborating with operations personnel, and contributing to the overall success of the program. 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 as we may have flexibility to adjust lectures days/times. Dates : June 1, 2026 - October 28, 2026 Frequency: Every Monday & Wednesday Time: 1:00 PM - 3:00 PM EST / 19:00 - 21:00 CEST Virtual Classroom Leadership: Prepare and lead virtual classroom sessions for a range of learners, which may vary in size from 20 to 8,000+. Deliver instruction on skills tailored to Learners' needs and data labeling needs Oversee the management of class time Q&A and monitor chat flow, and overall class energy and engagement dynamics Collaboration: Collaborate closely with Correlation One operations personnel to ensure smooth program delivery and adherence to schedules. Be flexible in contributing to classes during weekdays, as program schedules vary. Assist in lesson design, development, and improvement which may include tracking edits, suggestions, or changes to curriculum as needed Expectations: In addition to the core responsibilities, Lead Instructors are expected to adhere to the following expectations: Professionalism: Interact professionally with learners, Correlation One staff, additional contractors, and guest speakers, maintaining a high level of courtesy and respect. Lecture Preparation: Diligently and adequately prepare for lectures to ensure the delivery of high-quality content. Dynamic Online Presence Responsiveness and Empathy: Be highly responsive and empathetic to learners, providing thoughtful answers and assistance throughout the lesson Adjust the lesson pace and presentation to meet the needs of diverse learners while also maintaining responsibility for timely delivery of the prepared content. Exhibit an energy, pacing, and ability to make complex topics accessible and maintain strong learner engagement Communication: Communicate respectfully, recognizing that online or written communication may lack tone. Maintain extra communicative contact with Correlation One personnel. Positive Attitude: Foster a healthy learning environment by maintaining a positive attitude and promoting a culture of learning. Course Improvement: Contribute to course improvement by providing thoughtful and transparent feedback to the Correlation One team (before and after delivery). Bilingual Proficiency required for Machine Learning Data Associate 1 program: Deliver all instruction and learner support in German; use English professionally to collaborate with the C1 team (written updates, alignment meetings, issue escalation, and clarifications). Technical ML Knowledge: Strong working knowledge of the ML lifecycle - from data collection and model training to evaluation and deployment - sufficient to explain how labeling decisions affect model behavior and downstream outputs, without requiring learners to build models themselves. Generative AI & Foundation Model Expertise: Practical understanding of how large language models and multimodal foundation models work, including pre-training, fine-tuning, RLHF, and the role of human feedback in model alignment - able to connect these concepts directly to the annotator's role. Prompt Engineering Proficiency: Hands-on experience designing, evaluating, and iterating on prompts across zero-shot, one-shot, and few-shot paradigms; able to teach learners how to interpret prompt requirements, extract task constraints, and assess output quality against task intent. RAG & Applied AI Workflow Awareness: Working knowledge of Retrieval-Augmented Generation (RAG) pipelines and how they are used in production AI systems; able to

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