AI Engineer (Machine Learning / Generative AI) Startup

Company OverviewWe 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 SummaryYou 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.ResponsibilitiesDevelop and implement AI, Machine Learning, and Generative AI solutions to enhance product capabilitiesDesign 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 efficiencyBuild and maintain scalable AI services and APIs integrated with backend systemsProcess and manage both structured and unstructured data to support AI functionalitiesEnsure system architecture supports scalability and reliability of AI featuresConduct model testing and monitor performance metrics to ensure qualityTroubleshoot issues and implement improvements to enhance model accuracy and robustnessImplement feedback loops to continuously refine AI models based on user and system dataCollaborate effectively with product and engineering teams to align AI development with business goalsFollow best practices in coding and documentation to maintain high-quality software standardsParticipate actively in code reviews to ensure code quality and knowledge sharingRequired competencies and certificationsBachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related fieldProficient in Python programming and software engineering fundamentalsExperience in building APIs and backend systemsUnderstanding of machine learning conceptsFamiliarity with RESTful APIs and database systemsAbility to work independently with effective communication skillsPreferred competencies and qualificationsExperience with large language models (LLMs), prompt engineering, embeddings, or retrieval-augmented generation (RAG)Familiarity with deep learning frameworks such as PyTorch or TensorFlowExperience with cloud platforms including AWS, GCP, or AzureKnowledge of containerization (Docker), continuous integration/continuous deployment (CI/CD), or MLOps practicesExperience working with vector databases