This is a fantastic opportunity for a SENIOR MACHINE LEARNING ENGINEER to join a growing AI & Machine Learning team building production machine learning products that operate at global scale.
This role is based in either CAPE TOWN or DURBAN paying R1.2 – 1.5M PA.
THE COMPANY:
This global technology business develops the platforms behind some of the world’s leading online gaming brands, building highly scalable software used by millions of users across multiple international markets. They operate in a high-volume environment, processing massive amounts of real-time data and solving complex technical challenges at scale.
You’ll join a growing AI & Machine Learning team developing production machine learning products used across the business. Working across multiple business domains, you’ll contribute to a diverse portfolio of machine learning products and AI initiatives.
THE ROLE:
As a Senior Machine Learning Engineer, you’ll work with large-scale production datasets, developing machine learning models that become part of software products used by millions of users across multiple international markets.
Working alongside AI Engineers, Data Engineers and Software Engineers, you’ll take ownership of the full machine learning lifecycle, building classical machine learning and deep learning solutions from concept through to deployment, monitoring and continuous optimisation in production.
You’ll contribute to a broad portfolio of machine learning initiatives across multiple business domains, giving you exposure to diverse technical challenges rather than a single product or application.
This is a hands-on engineering role suited to someone with a strong software engineering background who enjoys building production machine learning systems in a high-volume environment.
Tech stack: Python, SQL, PyTorch, Scikit-learn, XGBoost, Databricks, Spark/PySpark, Snowflake, AWS.
THE REQUIREMENTS:
Bachelor’s degree in Computer Science, Data Science, Statistics, Applied Mathematics or a related quantitative field, or equivalent professional experience
7+ years’ commercial software engineering and/or ML engineering experience
Strong Python and SQL
Commercial experience building, training and deploying production ML models
Strong experience with data cleaning, feature engineering and data modelling
Experience with deep learning and ML frameworks such as PyTorch, Scikit-learn and XGBoost
Experience with production-grade ML pipelines and MLOps
Experience deploying ML solutions into AWS