Production ML Engineer – Regulated Analytics & AI Ops

Momentum; Cape Town; On-site; ZAR 900,000 - 1,300,000; Full time

Job summary

Momentum Corporate seeks an experienced ML Engineer to productionise advanced analytics and AI models. You will transform actuarial prototypes into scalable production systems, partnering with Actuarial, Data Science, and IT to ensure reliability and explainability in a regulated insurance context.

You will drive CI/CD for ML, manage batch and API deployments, and foster governance and cost efficiency across compute and storage while collaborating with cross-functional teams.

Qualifications

• Degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or related field (or equivalent).
• 3+ years’ experience in ML engineering, production data science, or platform engineering with deployment in production.
• 2+ years’ experience in regulated environments (insurance/financial services) with audit trails and explainability.
• Experience with model CI/CD, packaging (containers/conda), model & data versioning, monitoring/alerting.
• Experience building batch scoring pipelines and real-time inference (APIs, queues).
• Experience operating production ML workloads with monitoring, logging, alerting, and runtime optimisation.
• Proficiency in Python and SQL; ML libraries scikit-learn; familiarity with PyTorch and/or Keras.
• Cloud ML platforms: Azure ML, AWS SageMaker or Databricks; MLflow for registry/tracking.
• Orchestration: Airflow / Azure Data Factory / similar.
• CI/CD: Git, GitHub/GitLab/Azure DevOps pipelines.
• Excellent technical and communication skills.
• Knowledge of financial products, insurance and retirement fund industry is advantageous.

Responsibilities

• Actively participates in design, build and deployment of ML solutions for production-ready services.
• Transform actuarial and data science prototypes into production-grade batch jobs and APIs.
• Establish CI/CD for ML pipelines with scalable scoring and appropriate architectures.
• Design, deploy, and operate ML pipelines leveraging Fabric artefacts (Lakehouse, Notebooks, Data Pipelines).
• Partner with Data Engineering and IT for reliable data inputs for training and scoring.
• Align with IT on standards and hybrid solutions; ensure governance by design.
• Support model explainability and auditability to meet regulatory expectations.
• Provide technical enablement to uplift production-ready practices within the analytics team.
• Maintain cost efficiency across compute, storage, and orchestration; monitor runtime costs.

Skills

Python

SQL

ML/AI

CI/CD

Model deployment

Airflow

Azure ML

Databricks

MLflow

Docker

Kubernetes

Git

Scikit-learn

PyTorch/Keras

Education

Degree in CS/Data Science/Engineering

Tools

Airflow

Azure ML

Databricks

MLflow

Git

Docker

Kubernetes

Job description

Momentum Corporate seeks an experienced ML Engineer to productionise advanced analytics and AI models. You will transform actuarial prototypes into scalable production systems, partnering with Actuarial, Data Science, and IT to ensure reliability and explainability in a regulated insurance context.

You will drive CI/CD for ML, manage batch and API deployments, and foster governance and cost efficiency across compute and storage while collaborating with cross-functional teams.