Senior Technical Trainer — Machine Learning
pbThis position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Technical Trainer — Machine Learning based in Italy. /b /p pWe are seeking a hands-on machine learning practitioner with a passion for teaching to design and deliver engaging technical courses for engineers. In this remote freelance role, you will help learners progress from core machine learning concepts to training and evaluating their own models through practical, lab-based learning. You will collaborate with curriculum specialists and production teams to develop clear lessons, hands-on exercises, and real-world demonstrations. The focus is on sharing your technical expertise through compelling scripts, video presentations, and lab walkthroughs rather than managing production tasks. The initial paid course project typically lasts around three months and can be completed alongside existing professional commitments. With flexible hours and a delivery plan agreed in advance, the opportunity may lead to further projects or a full-time position. /p br/ h3Accountabilities /h3 ul lipbDesign and develop course content: /b Collaborate with the curriculum team to define course structure, sections, lessons, practical labs, and notebooks that support progressive learning. /p /li lipbCreate hands-on learning experiences: /b Write detailed lab specifications for the dedicated lab development team, then test the completed environments to ensure they work as intended. /p /li lipbWrite engaging educational scripts: /b Develop short, story-driven video lessons of approximately six minutes each, making machine learning concepts accessible, intuitive, and relevant to engineers. /p /li lipbDeliver technical presentations: /b Narrate scripted lessons confidently in English and record demonstrations and lab-solution walkthroughs that reinforce key concepts. /p /li lipbApply practical machine learning expertise: /b Build course material grounded in real experience with training, evaluating, and deploying machine learning models. /p /li lipbIncorporate editorial feedback: /b Work through structured reviews,
particularly during the initial course section, and refine content to meet established quality and teaching standards. /p /li lipbCollaborate remotely: /b Coordinate with curriculum and production teams through weekly syncs and Slack, maintaining sufficient time-zone overlap with colleagues based in Europe and Asia. /p /li lipbFocus on teaching and technical content: /b Partner with the production team, which manages video editing, animation, lab infrastructure, and publishing. /p /li /ul h3Requirements: /h3 ul lipbHands-on machine learning experience: /b Demonstrated ability to train, evaluate, and ship models using frameworks such as scikit-learn, PyTorch, or TensorFlow. /p /li lipbStrong technical communication skills: /b Ability to explain machine learning concepts, including the reasoning behind different approaches, clearly to engineers who are new to the field. /p /li lipbExcellent English proficiency: /b Strong written and spoken English, with the ability to write natural scripts, deliver clear narration, and communicate confidently on camera. /p /li lipbA genuine passion for teaching: /b Evidence of enjoying knowledge-sharing through online courses, tutorials, technical talks, workshops, mentoring, or other educational activities. /p /li lipbCurrent technical knowledge: /b An active interest in machine learning developments and a commitment to continuously learning and improving. /p /li lipbPresentation confidence: /b Comfort presenting technical material on camera in a clear, engaging, and accessible way. /p /li lipbOpenness to feedback: /b Willingness to follow an established teaching methodology, collaborate with editors, and improve course content through structured feedback.
/p /li lipbPreferred qualifications: /b /p ul lipExperience publishing courses on platforms such as Udemy, Pluralsight, or Coursera, or creating educational content on YouTube. /p /li lipExperience writing a technical book or teaching at a university, bootcamp, or similar educational setting. /p /li lipPractical knowledge of fine-tuning, MLOps, or deploying machine learning models in production. /p /li lipCloud machine learning certifications related to AWS, Microsoft Azure, Google Cloud Platform, or Databricks. /p /li /ul /li /ul h3Benefits: /h3 ul lipbCompetitive project-based compensation: /b A fixed fee is agreed upfront for each course, based on its length and technical complexity, with competitive rates for advanced topics and exceptional instructors. /p /li lipbFlexible working arrangements: /b Work remotely from anywhere in the world, with no fixed weekly-hour requirement and a delivery schedule agreed in advance. /p /li lipbCompatible with existing commitments: /b Complete the initial freelance course project alongside your current job or other professional responsibilities. /p /li lipbDefined project scope: /b The initial course project typically takes around three months, providing a clear timeframe for planning and delivery. /p /li lipbPayment upon completion: /b Receive the agreed course fee when the completed course is delivered. /p /li lipbLong-term career potential: /b Successful collaboration may lead to additional course projects or a full-time opportunity as part of a growing trainer network. /p /li lipbDedicated production support: /b Focus on instructional content and teaching while the production team handles editing, animation, lab infrastructure, and publishing. /p /li lipbCollaborative remote environment: /b Work closely with curriculum and production specialists through regular team syncs and Slack communication. /p /li lipbProfessional visibility: /b Showcase your technical expertise and teaching ability by developing practical learning experiences for a broad engineering audience. /p /li /ul #J-18808-Ljbffr
particularly during the initial course section, and refine content to meet established quality and teaching standards. /p /li lipbCollaborate remotely: /b Coordinate with curriculum and production teams through weekly syncs and Slack, maintaining sufficient time-zone overlap with colleagues based in Europe and Asia. /p /li lipbFocus on teaching and technical content: /b Partner with the production team, which manages video editing, animation, lab infrastructure, and publishing. /p /li /ul h3Requirements: /h3 ul lipbHands-on machine learning experience: /b Demonstrated ability to train, evaluate, and ship models using frameworks such as scikit-learn, PyTorch, or TensorFlow. /p /li lipbStrong technical communication skills: /b Ability to explain machine learning concepts, including the reasoning behind different approaches, clearly to engineers who are new to the field. /p /li lipbExcellent English proficiency: /b Strong written and spoken English, with the ability to write natural scripts, deliver clear narration, and communicate confidently on camera. /p /li lipbA genuine passion for teaching: /b Evidence of enjoying knowledge-sharing through online courses, tutorials, technical talks, workshops, mentoring, or other educational activities. /p /li lipbCurrent technical knowledge: /b An active interest in machine learning developments and a commitment to continuously learning and improving. /p /li lipbPresentation confidence: /b Comfort presenting technical material on camera in a clear, engaging, and accessible way. /p /li lipbOpenness to feedback: /b Willingness to follow an established teaching methodology, collaborate with editors, and improve course content through structured feedback.
/p /li lipbPreferred qualifications: /b /p ul lipExperience publishing courses on platforms such as Udemy, Pluralsight, or Coursera, or creating educational content on YouTube. /p /li lipExperience writing a technical book or teaching at a university, bootcamp, or similar educational setting. /p /li lipPractical knowledge of fine-tuning, MLOps, or deploying machine learning models in production. /p /li lipCloud machine learning certifications related to AWS, Microsoft Azure, Google Cloud Platform, or Databricks. /p /li /ul /li /ul h3Benefits: /h3 ul lipbCompetitive project-based compensation: /b A fixed fee is agreed upfront for each course, based on its length and technical complexity, with competitive rates for advanced topics and exceptional instructors. /p /li lipbFlexible working arrangements: /b Work remotely from anywhere in the world, with no fixed weekly-hour requirement and a delivery schedule agreed in advance. /p /li lipbCompatible with existing commitments: /b Complete the initial freelance course project alongside your current job or other professional responsibilities. /p /li lipbDefined project scope: /b The initial course project typically takes around three months, providing a clear timeframe for planning and delivery. /p /li lipbPayment upon completion: /b Receive the agreed course fee when the completed course is delivered. /p /li lipbLong-term career potential: /b Successful collaboration may lead to additional course projects or a full-time opportunity as part of a growing trainer network. /p /li lipbDedicated production support: /b Focus on instructional content and teaching while the production team handles editing, animation, lab infrastructure, and publishing. /p /li lipbCollaborative remote environment: /b Work closely with curriculum and production specialists through regular team syncs and Slack communication. /p /li lipbProfessional visibility: /b Showcase your technical expertise and teaching ability by developing practical learning experiences for a broad engineering audience. /p /li /ul #J-18808-Ljbffr