Lead Instructor: Machine Learning Data Associate

Jobgether; Netherlands; On-site; EUR 28,000 - 83,000; Part time

Benefits offered by this job

Remote work in NL-friendly timezone

Part-time contract

Virtual-first environment

High-impact teaching

International collaboration

Curriculum involvement

Flexible scheduling

Inclusive environment

Job summary

Jobgether is seeking a Lead Instructor: Machine Learning Data Associate based in the Netherlands to deliver live German-language instruction on ML data workflows and AI concepts. You will collaborate in English with program teams, refine curriculum, and support hands-on learning activities in a virtual environment.

The role is part-time and remote, with scheduled sessions aligned to EST/CEST, and requires strong German and English communication, plus experience in live instruction and curriculum

Qualifications

• Fluency in German to deliver instruction and support; strong English for written communication and meetings.
• Solid understanding of the machine learning lifecycle from data collection to deployment.
• Knowledge of generative AI, foundation models, RLHF, and model alignment.
• Hands-on experience with prompt engineering and teaching others to interpret requirements.
• Familiarity with Retrieval-Augmented Generation (RAG) and AI workflows.
• Awareness of responsible AI, privacy, security, bias, and transparency.
• Experience delivering high-quality live virtual instruction to large audiences.
• Experience supporting technical curriculum development and labs.
• Strong communication, presentation, empathy, adaptability, and classroom management.
• Preferred: AWS Certified AI Practitioner (AIF-C01) or equivalent.

Responsibilities

• Lead live virtual classes for diverse learner groups, from 100 to 8,000+ participants, with strong engagement.
• Deliver German instruction on ML data workflows, generative AI, foundation models, prompt engineering, and related topics.
• Explain data labeling impact on model training, evaluation and deployment.
• Manage virtual classroom dynamics: Q&A, chat, pacing, and content delivery.
• Adapt teaching approaches for varied learner backgrounds and technical levels.
• Prepare thoroughly for each lecture, ensuring accurate and accessible delivery.
• Collaborate with English-speaking program teams to ensure smooth schedules and alignment.
• Contribute to curriculum design and continuous improvement of hands-on activities.
• Provide constructive feedback to strengthen course quality and outcomes.
• Maintain professional, respectful, and empathetic learner interactions.

Skills

German fluency

English proficiency

Machine learning lifecycle

Generative AI

Prompt engineering

RAG

Multimodal AI

Responsible AI

Live virtual instruction

Curriculum development

Communication

Preparation & professionalism

AWS certification (preferred)

Job description

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 Netherlands.

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.

Accountabilities

• 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, elevate 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.
• 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.