Senior ML Engineer: Scale AI & GenAI in Production

Sabenza IT & Recruitment; Johannesburg; On-site; ZAR 1,200,000 - 2,100,000; Full time

Job summary

Sabenza IT & Recruitment in Johannesburg seeks a hands-on Senior ML Engineer to take AI from development to production. You will deploy ML models, build data pipelines, and scale AI capabilities using Databricks, AKS and containerised architectures.

You will collaborate with data scientists, implement robust MLOps, and optimize AI platforms for performance and cost. A strong background in GenAI and open-source LLMs is essential for success.

Qualifications

• Hands-on experience delivering ML/AI from development to production.
• Strong background in Databricks, Azure, Kubernetes, MLOps and GenAI.
• Knowledge of production-grade AI platforms and APIs.

Responsibilities

• Productionise and deploy ML models and data pipelines on Databricks.
• Build and support AI Agents, GenAI & RAG solutions.
• Develop robust MLOps/CI/CD pipelines with automated testing, monitoring and governance.
• Deploy and optimise Open Source LLMs & AI models on AKS.
• Build scalable APIs & microservices to expose AI capabilities.
• Develop containerised solutions using Docker & Kubernetes.
• Monitor model performance, drift and reliability in production.
• Collaborate with Data Scientists to turn prototypes into production-ready solutions.
• Troubleshoot and scale AI/ML platforms for cost and performance.
• Mentor junior engineers and share engineering best practices.

Skills

Databricks

MLflow

Mosaic AI

Model Serving

AKS

Python

SQL

REST APIs

Docker

CI/CD

MLOps

GenAI

LLMs

RAG

Spark

Education

Degree in Computer Science, Engineering, Econometrics, Mathematical Statistics, Actuarial Science or related field

Job description

Sabenza IT & Recruitment in Johannesburg seeks a hands-on Senior ML Engineer to take AI from development to production. You will deploy ML models, build data pipelines, and scale AI capabilities using Databricks, AKS and containerised architectures.

You will collaborate with data scientists, implement robust MLOps, and optimize AI platforms for performance and cost. A strong background in GenAI and open-source LLMs is essential for success.