Senior ML Engineer: GenAI, MLOps, Databricks & AKS

Ovations Technologies; Johannesburg; Hybrid; ZAR 800,000 - 1,200,000; Full time

Job summary

Ovations Technologies is seeking a Senior ML Engineer for a 12-month contract in a hybrid Johannesburg setting. You will operationalize, scale, and manage production-grade ML, AI, and GenAI solutions, focusing on robust MLOps pipelines on Databricks and deploying AI Agents and RAG solutions.

The role emphasizes containerized models on Azure Kubernetes Service (AKS) with Docker, Kubernetes, and CI/CD practices, plus collaboration with Data Scientists to turn prototypes into enterprise assets.

Qualifications

• Bachelor's degree in a quantitative field (e.g., CS, Eng, Stats).
• Hands-on experience with Databricks, MLflow, and AKS using Docker/Kubernetes.
• Strong Python, SQL, and REST API development skills.
• Experience building automated CI/CD deployment pipelines and observability frameworks.

Responsibilities

• Productionize, automate, and monitor ML pipelines, model serving, and workflows using Databricks, MLflow, and Mosaic AI with full CI/CD practices.
• Build, deploy, and support GenAI applications, AI Agents, and Retrieval-Augmented Generation (RAG) solutions.
• Deploy and optimize open-source AI models and custom REST microservices on AKS using Docker and Kubernetes.
• Monitor model drift, health, performance, and infrastructure costs in production; resolve issues across APIs and pipelines.
• Partner with Data Scientists to transition prototypes into scalable, compliant enterprise assets.

Skills

MLOps

CI/CD

Production ML

GenAI

Education

Bachelor's or higher in a quantitative field

Tools

Databricks

MLflow

AKS

Docker

Kubernetes

Python

SQL

REST API

Job description

Ovations Technologies is seeking a Senior ML Engineer for a 12-month contract in a hybrid Johannesburg setting. You will operationalize, scale, and manage production-grade ML, AI, and GenAI solutions, focusing on robust MLOps pipelines on Databricks and deploying AI Agents and RAG solutions.

The role emphasizes containerized models on Azure Kubernetes Service (AKS) with Docker, Kubernetes, and CI/CD practices, plus collaboration with Data Scientists to turn prototypes into enterprise assets.