Machine Learning Engineer / MLOps Engineer

Overview

An exciting opportunity is available for a skilled Machine Learning Engineer / MLOps Engineer to join a fast-paced Data Solutions environment within a leading retail technology business. This role is ideal for a technically strong professional who enjoys building scalable, production-ready AI and machine learning solutions that deliver measurable business value.

The successful candidate will play a key role in bridging the gap between Data Science and Engineering by deploying, automating, and maintaining robust ML systems within a modern cloud-based environment.

Key Responsibilities

• Design, build, and maintain scalable machine learning pipelines and production ML systems.
• Productionalise machine learning models to ensure reliability, scalability, and performance.
• Develop backend services and APIs in Python to integrate ML models into business applications.
• Implement and manage end-to-end MLOps processes including model training, testing, deployment, monitoring, and optimisation.
• Work within cloud infrastructure environments, primarily Google Cloud Platform (GCP).
• Develop and optimise feature extraction processes and reusable Feature Store solutions.
• Collaborate closely with Data Scientists, Data Engineers, and cross-functional Agile teams.
• Monitor and maintain advanced analytics systems to ensure operational stability and performance.
• Drive automation and continuous improvement within the ML engineering ecosystem.

Required Skills & Experience

• Strong hands-on Python development experience.
• Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Practical experience with Docker and Kubernetes container technologies.
• Exposure to cloud platforms such as GCP, AWS, or Azure.
• Experience working with relational and NoSQL databases.
• Strong understanding of MLOps principles and CI/CD practices for machine learning systems.
• Experience working within Agile delivery environments.
• Ability to translate business requirements into scalable technical solutions.

Qualifications

• Bachelor's or Master's Degree in Computer Science, Data Science, Engineering, or a related quantitative field.

Experience Required

• Minimum 3+ years' practical experience within Machine Learning Engineering, MLOps, or related AI engineering environments.
• Proven experience building and deploying enterprise-scale ML solutions in production environments.

What's on Offer

• Opportunity to work on enterprise-scale AI and advanced analytics initiatives.
• Exposure to modern cloud and machine learning technologies.
• Collaborative, innovative, and delivery-focused environment.
• Hybrid working model based in Cape Town's Northern Suburbs.