Community Engagement jobs in United Kingdom

Overview

We are seeking an experienced Conversational AI Trainer to design, develop, and deliver comprehensive training programs focused on conversational AI and natural language processing (NLP). The ideal candidate has hands-on experience in building, deploying, and optimizing conversational AI systems and excels in explaining complex concepts to diverse learners. This role involves crafting engaging, interactive learning experiences for participants, conducting hands-on workshops, and continuously updating training content to reflect new advancements. You will play a pivotal role in upskilling professionals and teams in the fast-evolving field of conversational AI.

Responsibilities

1. Develop Training Programs and Materials

- Design training modules on conversational AI, covering foundational NLP, chatbot design, dialog management, language models, and voice assistants.

- Create presentations, hands-on exercises, real-world case studies, and assessments that cater to various proficiency levels.

2. Lead Interactive Training Sessions

- Conduct in-person and virtual training sessions, ensuring an engaging and interactive learning environment.

- Facilitate hands-on workshops that allow participants to design, build, and deploy conversational agents using popular platforms (e.g., Dialogflow, Rasa, Amazon Lex).

- Encourage active participation and provide real-time feedback and guidance.

3. Customize Content for Client and Industry Needs

- Collaborate with clients to understand their specific training needs, adapting content to suit industry requirements (e.g., e-commerce, healthcare, customer service).

- Ensure training covers industry best practices, compliance standards, and cutting-edge conversational AI techniques.

4. Stay Updated on Trends and Tools in Conversational AI

- Continuously research and integrate the latest advances in conversational AI, NLP, and machine learning.

- Incorporate advancements in large language models, multi-turn dialog systems, and sentiment analysis into training materials.

5. Evaluate Training Effectiveness and Learner Progress

- Develop assessment tools and gather feedback to measure participants' understanding, engagement, and overall training effectiveness.

- Refine training content and methods based on participant feedback and industry trends.

Qualifications

Education: Bachelor's or master's degree in computer science, Linguistics, Artificial Intelligence, or related fields.

Experience: Experience in AI or NLP, with conversational AI development.

Training Experience: Proven track record of delivering technical training on conversational AI topics to diverse audiences.

Technical Skills:

Strong knowledge of conversational AI platforms (e.g., Dialogflow, Microsoft Bot Framework, Rasa, Amazon Lex).

Proficiency with NLP tools and libraries (e.g., spaCy, NLTK, Hugging Face Transformers).

Practical experience with Python, RESTful APIs, and data preparation techniques for training dialog models.

Communication Skills: Exceptional communication and presentation skills, with the ability to make complex AI concepts accessible and engaging.

Problem-Solving: Ability to address learner questions effectively and offer solutions during hands-on activities.

Adaptability: Skilled in adapting training content and style for different industries, participant experience levels, and learning environments.

Preferred Qualifications

Certifications: Relevant AI/ML certifications, such as Google's Professional ML Engineer, AWS Machine Learning, or specialized NLP credentials.

Publications and Community Engagement: Contributions to AI publications, conference talks, or participation in AI communities.

Languages: Proficiency in additional languages, especially those relevant to multi-lingual NLP applications.