We are looking for a Junior AI / Machine Learning Engineer to join our team straight out of university. In this role, you will work with senior AI engineers and data scientists to build, integrate, and improve AI-powered features in our products — from LLM-based assistants and retrieval-augmented generation (RAG) systems to classical ML models. This is a learning-focused role: we care more about your fundamentals, curiosity, and ability to learn quickly than about prior industry experience.

• Model Development & Experimentation: Support the development, training, and evaluation of machine learning models under the guidance of senior engineers.
• LLM & Prompt Engineering: Help design, test, and iterate on prompts and pipelines for large language model use cases such as chatbots, summarisation, and classification.
• AI Feature Integration: Integrate AI capabilities into applications by building APIs, services, and workflows that connect models to product features.
• Data Preparation: Clean, label, and analyse datasets to support model training, evaluation, and ongoing quality improvements.
• Evaluation & Monitoring: Help build evaluation harnesses, run benchmarks, and monitor production AI features for accuracy, latency, and cost.
• Tooling & Automation: Contribute to internal tools, notebooks, and scripts that speed up experimentation and model iteration.
• Documentation: Document experiments, model behaviours, and integration steps so findings can be reproduced and shared.
• Continuous Learning: Keep up with new models, papers, and frameworks; share learnings with the team through internal demos and discussions.

• A bachelor's or master's degree in Computer Science, Data Science, AI/Machine Learning, Statistics, or a related field (recent graduate or graduating within the next 6 months).
• Strong programming fundamentals in Python.
• Foundational understanding of machine learning concepts: supervised vs. unsupervised learning, training/validation/test splits, overfitting, and basic evaluation metrics.
• Exposure to common ML/DL libraries such as scikit-learn, PyTorch, or TensorFlow through coursework or personal projects.
• Comfortable with data manipulation libraries such as Pandas and NumPy.
• Familiarity with Git and collaborative development workflows.
• Strong problem-solving skills, intellectual curiosity, and the ability to communicate technical ideas clearly.
• Blockchain experience is a must.

• Personal projects, capstone work, or competitions (e.g., Kaggle) involving ML, NLP, or computer vision.
• Exposure to LLM tooling such as the OpenAI API, Anthropic API, Hugging Face Transformers, or LangChain / LlamaIndex.
• Familiarity with vector databases (e.g., Pinecone, Weaviate, pgvector) or basic RAG concepts.
• Basic experience building REST APIs (e.g., FastAPI, Flask) to serve model outputs.
• Awareness of MLOps concepts: experiment tracking, model versioning, and deployment (Docker, basic CI/CD).
• Exposure to cloud platforms (AWS, Azure, or GCP) is a plus.
• Strong written and verbal communication skills, and a thoughtful approach to AI safety and responsible use.

Email careers@qore3.com with the role title in the subject line. Attach your CV (PDF preferred) and a short note — one or two paragraphs — covering why this role and what you've built that you're proud of. Links to repos, products, or writing welcome. We read everything; expect a reply within five business days.