Machine Learning Engineer

Novah-LOY Consulting; Johannesburg; Hybrid; ZAR 700,000 - 1,200,000; Full time

Benefits offered by this job

Medical aid contribution

Annual bonuses

Performance-driven incentives

Job summary

Novah-LOY Consulting seeks a Machine Learning Engineer to lead development and deployment of AI models in a hybrid work environment. You will build scalable ML platforms on Azure using AKS, Databricks, Spark, Airflow, and MLflow to deliver production-grade solutions.

A STEM degree with 3–7 years in data science or cloud roles is required, along with strong Python and ML tooling knowledge. You will implement MLOps and design inference systems supporting APIs, batch, and real-time processing.

Qualifications

• STEM degree with 3–7 years in data science or cloud roles.
• Proven track record delivering production-ready AI projects.
• Strong knowledge of Microsoft Azure, Flo, MLflow, and Python.

Responsibilities

• Lead the development and deployment of advanced AI models.
• Design and implement scalable ML platforms on Azure (AKS, Databricks, Spark, Airflow, MLflow).
• Apply MLOps to automate deployment, monitoring, and model lifecycle management.

Skills

Azure cloud

AKS

Databricks

Spark

Airflow

MLflow

Python

R

MLOps

APIs

Real-time streaming

Education

STEM degree

Tools

Databricks

ML tooling

Job description

Are you driven by the challenge of transforming complex data into impactful machine learning solutions that propel business growth? Our client, a leading player in the technology and financial sectors, is seeking a highly skilled Machine Learning Engineer to join their innovative team. This role offers the opportunity to lead the development and deployment of advanced AI models within a dynamic, hybrid work environment, backed by competitive compensation and comprehensive employee benefits.

In this role, you will demonstrate your expertise in cloud architecture on Azure, utilizing tools such as AKS, Databricks, Spark, Airflow, and MLflow to build scalable, reliable machine learning platforms. Your strong data science literacy will bridge the gap between model development and production, while your programming proficiency in Python and R will facilitate data manipulation, statistical analysis, and model implementation. You will implement MLOps practices to streamline deployment, monitoring, and management of models, automating the entire pipeline from data ingestion to model lifecycle management. Designing robust inference systems—including APIs, batch, and real-time streaming solutions—and leveraging GPU acceleration for deep learning are key components of this strategic role.

To qualify, you should possess a STEM qualification, with between three and seven years of experience in data science or cloud-based roles. A proven track record of delivering successful projects into production is essential. You must have strong knowledge of Microsoft Azure, Flo, MLflow, and Python. Nice-to-have skills include experience in finance, banking, IT, or engineering sectors.

Our client offers a supportive work culture with opportunities for professional growth. Benefits include medical aid contribution, provident fund contributions, annual bonuses, and performance-driven incentives.