Hybrid MLOps Engineer — Queenstown (Production-Scale ML)

Placements24; East London; Hybrid; ZAR 600,000 - 900,000; Full time

Benefits offered by this job

Hybrid work model

Continuous learning

Competitive salary

Health coverage

Team collaboration

Job summary

Placements24 in Queenstown offers a hybrid AI/ML Operations Engineer role bridging ML development and production deployment. You will build and manage pipelines, infrastructure, and tools to enable scalable, reliable deployment and retraining of ML models, in collaboration with data scientists and software engineers.

The role requires a Bachelor's degree in a technical field and 3+ years in DevOps/SRE/MLOps, with cloud and containerization experience.

Qualifications

• Bachelor's degree in a related technical field.
• 3+ years of experience in DevOps, SRE, or MLOps with focus on ML systems.
• Proficiency in cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes).
• Experience with scripting languages (Python, Bash) and CI/CD tooling.
• Understanding of ML workflows and model lifecycle management.

Responsibilities

• Design, build, and maintain CI/CD pipelines for ML models.
• Manage infrastructure for training, deploying, and monitoring models in production.
• Automate model retraining, versioning, and deployment processes.
• Develop monitoring to track model performance, data drift, and system health.
• Collaborate with data scientists to optimize models for scalability and efficiency.

Skills

DevOps

MLOps

Cloud platforms

Python

Bash

Education

Bachelor's degree in CS/Engineering

Tools

Docker

Kubernetes

CI/CD tools

Job description

Placements24 in Queenstown offers a hybrid AI/ML Operations Engineer role bridging ML development and production deployment. You will build and manage pipelines, infrastructure, and tools to enable scalable, reliable deployment and retraining of ML models, in collaboration with data scientists and software engineers.

The role requires a Bachelor's degree in a technical field and 3+ years in DevOps/SRE/MLOps, with cloud and containerization experience.