Lead Instructor: Machine Learning Data Associate

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Instructor: Machine Learning Data Associate based in Germany.

This is an opportunity to lead engaging, high-impact virtual learning experiences for diverse audiences developing skills in machine learning and AI data workflows. You will deliver live technical instruction in German while collaborating professionally in English with program and operations teams. The role combines technical expertise, instructional leadership, and the ability to make complex AI concepts practical and accessible. You will help learners understand how data labeling influences machine learning systems, generative AI, multimodal models, and applied AI workflows. Sessions may range from smaller groups to audiences of thousands of learners in a highly interactive online environment. You will also contribute to curriculum refinement and continuous course improvement. This is a part-time contract position with a remote setup and scheduled sessions aligned with the EST/CEST time zones.

• Lead and facilitate live virtual classes for diverse learner groups, potentially ranging from 100 to more than 8,000 participants, while maintaining strong engagement and an effective learning environment.
• Deliver technical instruction in German on machine learning data workflows, generative AI, foundation models, prompt engineering, RAG, multimodal AI, responsible AI, and related concepts.
• Explain how data collection, annotation, labeling decisions, model training, evaluation, and deployment are connected, helping learners understand the downstream impact of their work.
• Manage virtual classroom dynamics, including Q&A, chat activity, pacing, learner engagement, and timely delivery of planned content.
• Adapt instructional approaches, explanations, and lesson pacing to accommodate learners with different backgrounds and levels of technical understanding.
• Prepare thoroughly for each lecture and ensure that technical content is delivered accurately, clearly, and in an accessible manner.
• Collaborate with program and operations teams in English to support smooth delivery, communicate updates, escalate issues, and maintain alignment on schedules and learner needs.
• Contribute to curriculum design and continuous improvement, including suggesting edits, refining lessons, and supporting the development of hands-on learning activities.
• Provide constructive feedback before and after sessions to strengthen course quality and learner outcomes.
• Maintain a professional, respectful, responsive, and empathetic presence when interacting with learners, colleagues, contractors, and guest speakers.

Requirements:

• Fluency in German sufficient to deliver all instruction and learner support professionally, combined with strong English proficiency for written communication, meetings, alignment, and issue escalation.
• Strong practical understanding of the machine learning lifecycle, including data collection, model training, evaluation, and deployment, with the ability to explain how labeling decisions affect model behavior and downstream outputs.
• Solid knowledge of generative AI and foundation models, including concepts such as pre-training, fine-tuning, reinforcement learning from human feedback (RLHF), and human feedback for model alignment.
• Hands-on experience with prompt engineering, including zero-shot, one-shot, and few-shot prompting, and the ability to teach learners how to interpret requirements, identify task constraints, and evaluate output quality.
• Working knowledge of Retrieval-Augmented Generation (RAG) and production AI workflows, including the ability to explain how to assess outputs for relevance, faithfulness, and groundedness.
• Understanding of multimodal and cross-modal AI, including how models process and generate text, images, audio, and video, and how these capabilities influence annotation and evaluation tasks.
• Knowledge of responsible AI, privacy, confidentiality, security, bias awareness, and transparency principles relevant to data labeling and AI workflows.
• Demonstrated experience delivering high-quality live virtual instruction, ideally to large and diverse audiences.
• Experience supporting technical curriculum development, lesson refinement, skills labs, or similar instructional content.
• Strong communication, presentation, empathy, adaptability, and classroom-management skills, with the ability to make complex technical concepts easy to understand.
• A positive and collaborative mindset, with strong attention to preparation, professionalism, responsiveness, and continuous improvement.
• Preferred: AWS Certified AI Practitioner (AIF-C01) certification or equivalent expertise, particularly experience aligning training content with certification domains and supporting exam readiness.

Benefits:

• Remote work: Work remotely from Romania or another location compatible with the required time zone.
• Part-time contract: Flexible engagement structured around scheduled instructional sessions and program needs.
• Virtual-first environment: Deliver impactful learning experiences entirely online using modern virtual classroom tools.
• High-impact teaching: Reach diverse learner populations and contribute to workforce development in AI and data.
• Professional collaboration: Work alongside program, operations, and instructional teams in an international environment.
• Curriculum involvement: Contribute ideas and expertise to the development and continuous improvement of technical training content.
• Potential schedule flexibility: Program dates and lecture times may be adjusted depending on program requirements and instructor availability.
• Inclusive environment: Participate in a learning culture focused on respect, accessibility, diversity, and equal opportunity.