Senior Data Scientist (ML Engineer)

About the role

As a Senior Data Scientist (ML Engineer) you will build, deploy, scale and support machine learning, AI and Generative AI solutions in production. The role focuses on operationalising models, developing AI applications and agents, and creating the platforms and services required to deliver business value at scale.

Key responsibilities

• Productionise, deploy and monitor machine learning models and data‑science pipelines on Databricks.
• Build, deploy and support AI agents, GenAI applications and RAG solutions on Databricks.
• Develop reusable ML pipelines using MLOps principles, including CI/CD, automated testing, monitoring and governance.
• Deploy, optimise and manage open‑source AI and machine‑learning models on Azure Kubernetes Service (AKS).
• Design, develop and support custom APIs and micro‑services on AKS to expose AI capabilities to business applications.
• Monitor model performance, drift, reliability and operational health in production environments.

Required profile

• Degree in Computer Science, Engineering, Econometrics, Mathematical Statistics, Actuarial Science; Masters or Doctorate is an advantage.
• Relevant certifications such as Microsoft Azure (AZ‑104, AZ‑305, AI‑102), Databricks, Kubernetes (CKA, CKAD) or similar are preferred.

Required skills

• Python programming
• SQL and API development
• Databricks, MLflow, model serving
• Azure Kubernetes Service (AKS)
• Kubernetes and Docker containerisation
• CI/CD pipelines and MLOps practices
• Spark and large‑scale distributed data processing
• Large language models (LLMs), Retrieval‑Augmented Generation (RAG) and Generative AI concepts