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 value
• Researching 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 integration
• Building frontend interfaces and user experiences for AI-powered applications
• Documenting changes to existing products
• Reviewing and implementing fixes for reported security vulnerabilities.

Requirements

• Minimum 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 classification
• Familiar 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 strategies
• Proficient in git, SQL
• Proficiency 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 AWS
• Experience in Docker/Kubernetes
• Experience 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 systems
• Strong presentation skills and ability to explain technical concepts clearly to a non-technical audience
• Proficiency in statistical software tools (e.g. R, SAS).