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- Tasks: Train and mentor aspiring ML Engineers in practical AI and ML skills.
- Company: Join a global leader in Data & AI training, shaping the future of tech education.
- Benefits: Enjoy remote work flexibility, a competitive salary, and a 4-day work week option.
- Why this job: Make a real impact by developing the next generation of ML professionals while staying updated with cutting-edge tech.
- Qualifications: Strong Python coding skills and experience in ML concepts; teaching experience is a plus.
- Other info: Cloud training provided; engage with diverse learners across various industries.
The predicted salary is between 39000 - 65000 £ per year.
Location: Fully Remote
Job Type: Permanent
Role Overview:
FIND are working with a Global Data & AI Training/Education specialist who are looking to expand their Data Science Training team. They’re looking for AI & ML Engineering specialists interested in becoming Trainers/Educators to junior/apprentice ML Engineers. This role is ideal for someone who enjoys teaching, mentoring & developing the next generation of ML professionals, while staying engaged with all the current & latest AI technologies and best practices.
Key Responsibilities:
- Deliver high-quality, practical training sessions in Machine Learning and Artificial Intelligence Engineering.
- Facilitate both beginner and advanced-level content to AI / ML Engineers and Data Scientists working across a variety of companies & industries.
- Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc).
- Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you).
- Keep training material up to date with current Data Science / AI / ML industry trends, tools, and techniques.
- Support learners with career development and technical confidence.
Required Skills & Experience:
- Strong coding experience in Python and the ML/AI development ecosystem.
- Solid understanding and ideally hands-on experience with core Machine Learning concepts.
- Specialisation or strong exposure to NLP, LLMs, Gen AI OR Deep Learning frameworks (one area is fine).
- Prior experience delivering training, mentoring, or leading workshops or lectures (Trainer / Instructor / Lecturer / Teacher Consultant / Coach / Mentor / Educator).
- Ability to explain complex topics clearly and adapt to different learning levels.
Desirables:
- Familiarity with modern MLOps practices, reproducibility, and collaborative workflows.
- Practical experience deploying or training models in cloud environments (AWS, GCP or Azure).
This is a fully remote working position & salary is £65,000, with the option to work 4 days a week.
Please get in touch for more info! Ryan.hammond@wearefind.co.uk
Machine Learning Engineer Trainer employer: FIND | Creating Futures
Contact Detail:
FIND | Creating Futures Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer Trainer
✨Tip Number 1
Make sure to showcase your passion for teaching and mentoring in any conversations you have. Highlight experiences where you've successfully guided others in their learning journey, as this role is all about developing the next generation of ML professionals.
✨Tip Number 2
Stay updated with the latest trends in AI and ML technologies. Being knowledgeable about current tools and practices will not only help you in training but also demonstrate your commitment to continuous learning, which is crucial for this position.
✨Tip Number 3
Prepare to discuss your hands-on experience with Python and relevant ML libraries during interviews. Be ready to share specific examples of projects you've worked on, as practical experience is key for this role.
✨Tip Number 4
Familiarise yourself with cloud-based tools and services like AWS, GCP, or Azure. Even if you haven't used them extensively, showing a willingness to learn and adapt to these environments can set you apart from other candidates.
We think you need these skills to ace Machine Learning Engineer Trainer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in Machine Learning and AI, especially any teaching or mentoring roles you've held. Use specific examples to demonstrate your coding skills in Python and familiarity with ML libraries.
Craft a Compelling Cover Letter: In your cover letter, express your passion for teaching and mentoring the next generation of ML professionals. Mention any relevant experience you have in delivering training or workshops, and how you stay updated with the latest industry trends.
Showcase Relevant Projects: If you have worked on any projects related to Machine Learning or AI, include them in your application. Highlight your role, the technologies used, and the impact of the project. This will demonstrate your practical experience and expertise.
Prepare for Potential Questions: Think about how you would explain complex ML concepts to beginners. Be ready to discuss your teaching philosophy and how you adapt your methods to different learning levels. This will show your suitability for the trainer role.
How to prepare for a job interview at FIND | Creating Futures
✨Showcase Your Teaching Skills
Since the role involves training and mentoring, be prepared to demonstrate your teaching abilities. You might be asked to explain a complex ML concept or walk through a coding example. Practise explaining topics clearly and concisely.
✨Highlight Relevant Experience
Make sure to discuss any previous experience you have in delivering training or mentoring. Share specific examples of workshops or lectures you've led, and how you adapted your content for different audiences.
✨Stay Updated on Industry Trends
The field of AI and ML is constantly evolving. Be ready to discuss the latest trends, tools, and techniques in the industry. This shows your passion for the subject and your commitment to providing up-to-date training.
✨Prepare for Technical Questions
Expect technical questions related to Python, ML concepts, and cloud services. Brush up on your knowledge of libraries like Scikit-learn, TensorFlow, and PyTorch, as well as MLOps practices. Being well-prepared will boost your confidence during the interview.
