Senior Technical Trainer — Machine Learning

Role Overview

Accountabilities

• Design and develop course content: collaborate with the curriculum team to define course structure, sections, lessons, practical labs, and notebooks.
• Create hands-on learning experiences: write detailed lab specifications for the lab development team and test completed environments.
• Write engaging educational scripts: develop short, story-driven video lessons of approximately six minutes each.
• Deliver technical presentations: narrate scripted lessons confidently in English and record demonstrations and lab-solution walkthroughs.
• Apply practical machine learning expertise grounded in real experience training, evaluating, and deploying models.
• Incorporate editorial feedback, particularly during the initial course section, to meet quality and teaching standards.
• Collaborate remotely with curriculum and production teams through weekly syncs and Slack, with time-zone overlap with Europe and Asia.
• Focus on teaching and technical content while the production team handles video editing, animation, lab infrastructure, and publishing.

Requirements

• Hands-on machine learning experience training, evaluating, and shipping models using frameworks such as scikit-learn, PyTorch, or TensorFlow.
• Strong technical communication skills to explain machine learning concepts clearly to engineers new to the field.
• Excellent English proficiency with strong written and spoken English and confidence on camera.
• A genuine passion for teaching, evidenced by online courses, tutorials, technical talks, workshops, or mentoring.
• Current technical knowledge and commitment to continuous learning in machine learning.
• Comfort presenting technical material on camera in a clear, engaging, accessible way.
• Openness to feedback and willingness to follow an established teaching methodology.

Preferred Qualifications

• Experience publishing courses on platforms such as Udemy, Pluralsight, or Coursera, or creating educational content on YouTube.
• Experience writing a technical book or teaching at a university, bootcamp, or similar educational setting.
• Practical knowledge of fine-tuning, MLOps, or deploying machine learning models in production.
• Cloud machine learning certifications related to AWS, Microsoft Azure, Google Cloud Platform, or Databricks.

Benefits

• Competitive project-based compensation: a fixed fee agreed upfront per course based on length and technical complexity.
• Flexible working arrangements: work remotely from anywhere with no fixed weekly-hour requirement and a delivery schedule agreed in advance.
• Compatible with existing commitments: complete the initial freelance course project alongside a current job.
• Defined project scope: the initial course project typically takes around three months.
• Payment upon completion: receive the agreed course fee when the completed course is delivered.
• Long-term career potential: successful collaboration may lead to additional projects or a full-time opportunity.
• Dedicated production support for editing, animation, lab infrastructure, and publishing.
• Collaborative remote environment with regular team syncs and Slack communication.
• Professional visibility by developing practical learning experiences for a broad engineering audience.

Application Notes

• Position is listed by Jobgether on behalf of a partner company that manages all applications and next steps.
• Jobgether uses an AI-powered matching process to shortlist candidates; final decisions are managed by the hiring company's internal team.