Engineer : AI / ML

Job category : FMCG, Retail, Wholesale and Supply Chain

Location : Cape Town

Contract : Permanent

Remuneration : Market Related

EE position : No

Introduction

The AI / ML Engineer will be responsible for operationalizing AI / ML models developed by the Data Science team, ensuring their seamless integration into production environments. This role focuses on deploying, monitoring, and maintaining AI / ML models, optimising system performance, and automating MLOps processes to enhance scalability and reliability.

• Deploy and operationalize AI / ML models developed by the Data Science team into scalable production environments.
• Develop and maintain robust machine learning pipelines to enable efficient model inference and data transformation.
• Ensure seamless integration of AI / ML models with enterprise applications and data systems.
• Implement MLOps best practices, including CI / CD for machine learning, model versioning, monitoring, and automated retraining.
• Optimize AI / ML workflows for performance, cost efficiency, and resilience.
• Collaborate with data engineers to ensure data pipelines support AI / ML model inference and training.
• Leverage cloud-based AI / ML services (AWS SageMaker, Lambda, Glue, etc.) to streamline model deployment and automation.
• Implement AI-driven monitoring and alerting mechanisms to detect model drift and performance degradation.
• Work closely with business stakeholders to ensure AI / ML models are delivering expected value.
• Ensure AI / ML solutions adhere to best practices for security, compliance, and governance.
• Provide technical support and troubleshoot AI / ML model issues in production environments.
• Bachelor’s degree in computer science, Engineering, or a related field with 4 - 5 years of experience in operationalising AI / ML models in production environments.
• Strong understanding of AI / ML deployment strategies, including containerization, orchestration, and inference optimisation.
• Experience with implementing MLOps principles, including CI / CD pipelines, automated model monitoring, and retraining.
• Proficiency in Python, with experience in AI / ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Expertise in data engineering tools and frameworks such as Apache Spark, AWS Glue, and SQL.
• Practical experience with AWS services, including SageMaker, Lambda, S3, IAM, and RDS.
• Experience working with structured and unstructured data within enterprise environments.
• Strong software development skills, with experience in version control systems such as Git.
• Familiarity with containerisation and orchestration tools (Docker, Kubernetes) for AI / ML workloads.
• Knowledge of cloud security, data governance, and compliance considerations.
• Excellent verbal and written communication skills; must work well in an agile, collaborative team environment.

ADDITIONAL CRITERIA

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