ML Engineer

Job Description About the Role

Cape Town / Johannesburg (Hybrid)

Responsibilities

• Demonstrate proven cloud experience on Azure with strong system/application architecture skills (including AKS, Databricks, Spark, Airflow, and MLflow expertise), alongside expert-level knowledge of data structures, algorithms, computability and complexity, and computer architecture, with practical experience using an enterprise feature store.
• Apply strong data science literacy - including understanding of model types, feature engineering, statistical principles, evaluation metrics, and common modelling workflows - to effectively bridge the gap between model development and production.
• Expert proficiency in programming tools (such as Python, R, etc.) for data manipulation, statistical analysis, model implementation, and production grade machine learning tasks is essential.
• Implement MLOps practices to streamline the deployment, monitoring, and management of machine learning models in production, ensuring reproducibility, scalability and model governance.
• Develop, maintain, and evolve a scalable, reliable machine learning platform that meets community and stakeholder needs, proactively resolving performance bottlenecks and optimizing resource usage across compute and storage layers.
• Automate the end-to-end machine learning pipeline , from data ingestion, feature engineering to model deployment, monitoring and lifecycle management.
• Design and build robust inference systems , such as APIs, batch processing, and real-time streaming solutions, to facilitate the deployment and utilization of machine learning models.
• Leverage GPU acceleration to enhance the performance and efficiency of machine learning models, particularly for deep learning tasks.
• STEM Qualification
• Engineering, Computer Science, Econometrics, Mathematical Statistics, Actuary Science
• Masters or Doctorate will be an added advantage

Requirements

• 3-7 years’ experience in a data science or cloud based role
• Portfolio of delivering projects successfully into production