Machine Learning/ AI Engineer

Responsibilities

• Build agentic AI systems: design, develop and deploy production‑grade agentic systems that power adaptive learning experiences — from multi‑step reasoning pipelines to autonomous feedback loops that respond to learner behaviour in real time.
• LLMs & RAG architectures: architect and integrate LLM‑powered features using retrieval‑augmented generation, prompt engineering strategies, and evaluation pipelines.
• Agentic frameworks: use LangChain and LangGraph to build reliable, observable multi‑agent workflows. Design agent orchestration patterns, tool use, memory, and state management for production environments.
• ML system development: collaborate with Senior ML Engineers and Data Scientists to move models from experimentation to production, including feature engineering, training pipelines, online inference, and monitoring.
• Platform & tooling: contribute to our ML infrastructure and experiment orchestration tools (MLFlo...