Key Facts

Remote From:

Internships

Entry-level / graduate

English

Hard Skills

Training Datasets Python (Programming Language) Learning Analytics Program Assessment Rating Tool Knowledge Base GPU Optimization Instructional Design Interactive Learning Continuous Improvement Process Curriculum Development Project Management

Other Skills

•
Communication
•
Leadership
•
Teamwork
•
Problem Solving

Roles & Responsibilities

Experience developing AI-driven educational tools or AI tutors
Expertise in designing and fine-tuning LLMs and creating training datasets
Proficiency in evaluating AI systems and implementing automated feedback mechanisms
Familiarity with building knowledge bases, hands-on labs, capstone projects, and peer-learning systems

Requirements:

Independently design and develop specialized LLM training protocols for each module of the AI Academy curriculum, from Python fundamentals to advanced topics like RAG systems and hardware optimization.
Create detailed training datasets and fine-tuning strategies to ensure AI tutors can serve as the primary instructional method across all technical domains.
Implement robust evaluation frameworks to assess AI tutor performance and learning outcomes, and develop automated feedback systems to replace traditional instructor assessment.
Develop knowledge bases and interactive problem-solving approaches to guide hands-on exercises and capstone projects, and establish systems for peer learning facilitation with continuous improvement based on student metrics.

Job description

We’re seeking an experienced AI developer to lead the development and implementation of AI tutors for the Universa AI Academy curriculum. This autonomous role will be responsible for transforming our comprehensive 6-month AI Engineering syllabus into fully AI-powered learning experiences, creating a self-guided educational system without human instructors.

Key Responsibilities

• Independently design and develop specialized LLM training protocols for each module of our AI Academy curriculum, from Python fundamentals to advanced topics like RAG systems and hardware optimization
• Create detailed training datasets and fine-tuning strategies to ensure AI tutors can serve as the primary instructional method across all technical domains
• Implement robust evaluation frameworks to assess AI tutor performance and learning outcomes
• Develop comprehensive automated feedback systems to replace traditional instructor assessment
• Create specialized knowledge bases that allow AI tutors to guide students through hands-on exercises and capstone projects with minimal human intervention
• Design interactive problem-solving approaches that mimic expert guidance
• Build systems for peer learning facilitation where AI tutors can moderate and guide student collaboration
• Implement continuous improvement processes based on student interactions and performance metrics

This is the final opportunity to join this program for free. Further cohorts will have only paid access to it. Don't miss it, join AI Revolution.

Ready to apply?

APPLY

Share ·