Machine Learning Engineer — Data Pipelines & MLOps

Badger Holdings (Pty) Ltd; George; Hybrid; ZAR 700,000 - 900,000; Full time

Job summary

Badger Holdings (Pty) Ltd, through ARC in George, Western Cape, is seeking a Machine Learning Engineer to build AI capabilities and partner with the Data Science team. The role focuses on reliable data provisioning with production-ready ML solutions and cloud-based infrastructure.

You will split time between data engineering and MLOps, deploying models, monitoring performance, and implementing best practices to scale AI across the insurance group.

Qualifications

• Experienced Machine Learning Engineer
• Strong data engineering and ML operations (MLOps) skills
• Ability to turn experimentation into production-ready AI solutions
• Collaborative partner to Data Science team for reliable data and deployment infrastructure

Responsibilities

• Build reliable data pipelines and feature datasets for model development
• Develop and maintain Snowflake assets powering models
• Deploy, monitor, and maintain ML models in production with engineering best practices

Job description

Data & AI | ARC | George, Western Cape (Hybrid negotiable) | Permanent

Build the engineering that brings AI to life.

At ARC, we're building the next generation of data, analytics and AI capabilities for Badger SA, including

Machine Learning Engineer

Data & AI | ARC | George, Western Cape (Hybrid negotiable) | Permanent

Build the engineering that brings AI to life.

At ARC, we're building the next generation of data, analytics and AI capabilities for Badger SA, including dotsure.co.za and Pacific International Insurance. Our purpose is simple: use intelligent technology to create Soft Landings, making work simpler, decisions smarter and businesses stronger.

We're looking for an experienced Machine Learning Engineer who enjoys solving real business problems through engineering excellence. You'll become the dedicated engineering partner to our Data Science team, ensuring they have reliable, high-quality data to build models and the infrastructure needed to deploy those models into production with confidence.

This is an opportunity to play a key role in shaping how AI is delivered across a growing insurance group, working with modern cloud technologies and influencing the future of our machine learning platform.

About The Role

As our Machine Learning Engineer, you'll operate at the intersection of Data Engineering and Machine Learning Operations (MLOps), turning experimentation into production-ready AI solutions.

Approximately 60% of your role will focus on building reliable data pipelines, feature datasets and Snowflake assets that power model development.

The remaining 40% will focus on MLOps, including deploying, monitoring and maintaining machine learning models in production while establishing engineering best practices.