Company Overview
We are an AI-driven technology company building a smart learning platform that transforms how students learn and solve problems. Our product leverages AI, including LLMs and intelligent content systems, to deliver personalised learning experiences.
Job Summary
You will design and build AI-powered features for our product, applying Machine Learning and Generative AI techniques to real-world applications such as LLM workflows, content intelligence, and system optimisation.
Responsibilities
- Develop and implement AI, Machine Learning, and Generative AI solutions to enhance product capabilities
- Design and build applications using large language models (LLMs), including prompting, embeddings, and retrieval-augmented generation (RAG)
- Optimise AI models for improved performance, reduced latency, and cost efficiency
- Build and maintain scalable AI services and APIs integrated with backend systems
- Process and manage both structured and unstructured data to support AI functionalities
- Ensure system architecture supports scalability and reliability of AI features
- Conduct model testing and monitor performance metrics to ensure quality
- Troubleshoot issues and implement improvements to enhance model accuracy and robustness
- Implement feedback loops to continuously refine AI models based on user and system data
- Collaborate effectively with product and engineering teams to align AI development with business goals
- Follow best practices in coding and documentation to maintain high-quality software standards
- Participate actively in code reviews to ensure code quality and knowledge sharing
Required competencies and certifications
- Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related field
- Proficient in Python programming and software engineering fundamentals
- Experience in building APIs and backend systems
- Understanding of machine learning concepts
- Familiarity with RESTful APIs and database systems
- Ability to work independently with effective communication skills
Preferred competencies and qualifications
- Experience with large language models (LLMs), prompt engineering, embeddings, or retrieval-augmented generation (RAG)
- Familiarity with deep learning frameworks such as PyTorch or TensorFlow
- Experience with cloud platforms including AWS, GCP, or Azure
- Knowledge of containerization (Docker), continuous integration/continuous deployment (CI/CD), or MLOps practices
- Experience working with vector databases
