ML Engineer

Remuneration: market-related |

Location:

George | Job level:
Mid | Type:
Permanent | Reference: #BH-475 | Company:
Badger Holdings

Machine Learning Engineer at ARC, Data & AI department, George, Western Cape (Hybrid negotiable), permanent role.

As a machine learning engineer, you will 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.

• Design and build scalable feature pipelines and training datasets for machine learning models.
• Develop and maintain high-quality data assets within Snowflake.
• Build reliable, monitored and well-documented data pipelines for model training and inference.
• Collaborate with data engineering teams to align with platform standards and architecture.
• Validate data quality and ensure consistency with business definitions.
• Apply data governance principles and regulatory requirements including POPIA, FAIS and TCF.

• Partner with Data Scientists to product ionise machine learning models.
• Build and maintain deployment pipelines and model serving infrastructure.
• Implement CI/CD processes for machine learning workflows.
• Manage model versioning, experiment tracking and reproducible deployments.
• Monitor models for performance, reliability and data drift.
• Maintain documentation, auditability and model lineage.
• Support responsible AI practices, including explainability and model governance.
• Troubleshoot production issues and continuously improve model performance.

• Help establish ML Engineering standards and best practices.
• Contribute to the architecture of our AI ecosystem across Azure and GCP.
• Work closely with Analytics Engineers to integrate machine learning into business solutions.
• Identify opportunities to improve automation, tooling and delivery.
• Proactively identify risks and recommend practical solutions.

• Bachelor's degree in computer science, data science, software engineering, information technology, mathematics, statistics or a related quantitative field.
• A postgraduate qualification in artificial intelligence, machine learning or data science will be advantageous.
• Relevant industry certifications in Azure, Google Cloud, Snowflake or Machine Learning are advantageous.

• 5+ years' experience in machine learning engineering, data engineering or a similar role.
• Proven experience deploying machine learning models into production.
• Strong Python development skills.
• Advanced SQL skills.
• Experience with Snowflake or another cloud data warehouse.
• Experience with Azure cloud services.
• Knowledge of Git, CI/CD pipelines and modern software engineering practices.
• Experience with Docker and containerisation.
• Experience building feature engineering pipelines.
• Understanding of model monitoring, observability and drift detection.
• Knowledge of data governance and regulatory frameworks such as POPIA and FAIS.

• Experience with dbt.
• Databricks experience.
• Feature Store implementation and management.
• API development and model serving.
• Experience with in insurance or financial services.
• Exposure to GCP environments.

• A collaborative engineer who enjoys partnering with data scientists.
• Passionate about building reliable, scalable machine learning solutions.
• Comfortable balancing data engineering with production ML engineering.
• Curious about emerging AI technologies and best practices.
• Pragmatic, solutions-focused and commercially aware.
• Someone who takes ownership and follows work through to completion.
• Committed to engineering quality, documentation and continuous improvement.

This is more than another machine learning role.

You'll have the opportunity to shape the future of AI within a growing…