Machine Learning Specialist_ Contract

Collaborating with business users to understand their key priorities and use cases; proposing and developing solutions using data science and/or Generative AI techniques to drive business valueResearching emerging AI/data science techniques and identifying relevant ones for EDB to explore and adopt (e.g., agentic, LLM, predictive, fraud/anomaly detection, text analytics, customer segmentation)Datawrangling & analysis - preprocessing, cleaning and feature engineering Supporting daily operations and maintenance of deployed data science models and products, including assistants on PAIR/AIBots Developing backend APIs and services to support AI model deployment and integrationBuilding frontend interfaces and user experiences for AI-powered applicationsDocumenting changes to existing productsReviewing and implementing fixes for reported security vulnerabilities.RequirementsMinimum of a bachelor's degree in computer science, computer engineering, machine learning/data science/AI or related disciplines;Able to tounderstand and apply a range of AI/ML techniques for regression and classificationFamiliar with popular Python packages (e.g., pandas, matplotlib, scikit-learn, XGBoost, NLTK, spaCy) Understanding of LLM concepts (e.g. context windows, embeddings, chunking, token management) and architectures (e.g. RAG) Experience with context engineering techniques and prompt optimisation strategiesProficient in git, SQLProficiency in business intelligence tools (e.g., Tableau, Qlik, MS Power BI, Microstrategy)\Bonus skillsets which will allow you to excel in this role include: Proficiency in modern programming languages (e.g., TypeScript, C#)Experience in cloud platform and services, preferably in AWSExperience in Docker/KubernetesExperience with web frameworks and full-stack development, including backend frameworks (e.g., FastAPI, Flask, Express.js) and RESTful API development, and frontend technologies (e.g., React, Vue.js, HTML/CSS, TypeScript)Experience with LLM frameworks (e.g., LangChain, LlamaIndex, Hugging Face Transformers)Knowledge of vector databases and embedding techniques (e.g. Pinecone, Chroma, FAISS)Understanding of AI agent frameworks and multi-agent systemsStrong presentation skills and ability to explain technical concepts clearly to a non-technical audience Proficiency in statistical software tools (e.g. R, SAS).