Cape Town: Machine Learning Engineer (Model Deployment or MLOps) (CPT Hybrid or Remote) posted by DataFin Recruitment

About the Role

A fast-paced FinTech company seeks a passionate Machine Learning Engineer (MLOps focus) to power instant lending decisions – no humans in the loop. Its models drive credit risk, portfolio management, and lifecycle decisioning with the biggest challenge being moving models from Data Science into reliable production systems. We’re looking for you to bridge that gap and ensure that every model built makes it into production fast, reliable, and cost-efficient.

Key Responsibilities

• Take models from Data Scientists (notebooks, prototypes) and productionize them into scalable APIs and pipelines.
• Build CI or CD pipelines for ML: automated testing, validation, deployment, rollback.
• Implement monitoring for data drift, model drift, and performance decay with automated alerts and retraining triggers.
• Maintain reproducible environments for training and inference (Docker, SageMaker, Lambda, Step Functions).
• Design AWS-native ML infrastructure optimized for cost and scale (ECS or EKS, SageMaker, Lambda, Glue, Step Functions, S3).
• Build ETL or ELT pipelines that prepare structured and nested JSON data from PostgreSQL (BI reporting) and other sources.
• Ensure models integrate seamlessly into real-time decisioning engines.
• Collaborate with Backend Engineers (Node.js or JavaScript) to integrate ML services into production systems.
• Build microservices & APIs for inference, feature engineering, and data transformations.
• Ensure low-latency, fault-tolerant services for real-time lending decisions.

Requirements

• Postgraduate Degree in a numerate discipline such as Statistics, Mathematics, Software Engineering, Computer Science, or a related field.
• Relevant AWS Certifications (e.g., AWS Certified Machine Learning Specialty, AWS Solutions Architect).
• MLOps-related Certifications or professional courses (e.g., Coursera, Udacity, or equivalent).
• 3+ Years experience in ML Engineering, Data Engineering, or Software Engineering with focus on ML deployment.
• Proven track record of deploying ML models into production (SageMaker, Lambda, Step Functions, or equivalent).
• Experience building CI or CD pipelines for ML.
• Strong Backend or Service Development skills (Node.js, Python, or JavaScript).
• Deep experience with AWS infrastructure (EC2, ECS or EKS, S3, Lambda, Glue, Step Functions).
• Strong SQL + PostgreSQL skills, including working with deeply nested JSON data.

Qualifications

• Completed Postgraduate Degree in a numerate discipline.

Salary & Benefits

The salary for this position is ZAR 12,000 – ZAR 18,000 per annum, depending on experience.