Machine Learning Engineer (Hybrid – Cape Town / Johannesburg)

Omega Human Capital; Johannesburg; Hybrid; ZAR 600,000 - 1,000,000; Full time

Job summary

Omega Recruitment – Career Opportunity: Machine Learning Engineer (Hybrid – Cape Town / Johannesburg) is seeking a skilled professional to design and operationalise production-grade ML systems, architect robust data and compute infrastructure, and enable high-performance deployments using Azure, Databricks, AKS, Spark, Airflow, and MLflow.

You will collaborate with data scientists to bridge model development and production, automate end-to-end ML pipelines, and build APIs for real-time inference

Qualifications

• 3–7 years’ experience in data science or cloud-based roles.
• Proven track record of delivering ML projects into production.
• Expert proficiency in Python/R and cloud-native ML tools.

Responsibilities

• Architect and deploy ML solutions in cloud environments (Azure).
• Implement MLOps practices for reproducibility, scalability, and governance.
• Automate end‑to‑end ML pipelines from ingestion to deployment.
• Build APIs, batch, and real‑time inference systems.
• Leverage GPU acceleration for deep learning tasks.
• Collaborate with data scientists to bridge model development and production.

Skills

Python

R

Education

STEM qualification (Computer Science, Engineering, Statistics, Econometrics, Actuarial Science)

Master’s/PhD advantageous

Tools

Azure

Databricks

AKS

Spark

Airflow

MLflow

Job description

Omega Recruitment – Career Opportunity: Machine Learning Engineer (Hybrid – Cape Town / Johannesburg)

At Omega Recruitment , we partner with leading organisations to connect top talent with transformative opportunities. We are currently searching for a Machine Learning Engineer to join a forward‑thinking team that is scaling enterprise‑grade AI systems to deliver measurable impact across industries.

The Role

As a Machine Learning Engineer, you will design and operationalise production‑grade ML systems, architect robust data and compute infrastructure, and enable high‑performance deployments using Azure, Databricks, AKS, Spark, Airflow, and MLflow . This role is ideal for professionals who thrive at the intersection of data science and engineering, with a passion for building scalable, reliable solutions.

Key Responsibilities

• Architect and deploy ML solutions in cloud environments (Azure).
• Implement MLOps practices for reproducibility, scalability, and governance.
• Automate end‑to‑end ML pipelines from ingestion to deployment.
• Build APIs, batch, and real‑time inference systems.
• Leverage GPU acceleration for deep learning tasks.
• Collaborate with data scientists to bridge model development and production.

Candidate Profile

• STEM qualification (Computer Science, Engineering, Statistics, Econometrics, Actuarial Science).
• Master’s/PhD advantageous.
• 3–7 years’ experience in data science or cloud‑based roles.
• Proven track record of delivering ML projects into production.
• Expert proficiency in Python/R and cloud‑native ML tools.