Senior MLOps Engineer – AI Pipelines & Cloud Infra

Placements24; Soweto; On-site; ZAR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Competitive salary

Medical aid

Retirement fund

Professional development opportunities

Job summary

Placements24 is seeking a Senior AI/ML Operations (MLOps) Engineer in Soweto, Gauteng, to streamline the machine learning lifecycle from development to deployment and monitoring. You will build and maintain robust infrastructure and pipelines enabling data science teams to deliver reliable AI solutions.

You will design scalable MLOps pipelines, implement CI/CD for ML workflows, and automate deployment and scaling on cloud platforms like AWS, Azure, and GCP.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• 5+ years in software engineering, DevOps, or site reliability with MLOps focus.
• Proficiency in Python, Go, or Java and hands-on cloud experience.

Responsibilities

• Design and maintain scalable MLOps pipelines for training, evaluation, deployment, and monitoring.
• Implement CI/CD practices for ML models and data pipelines.
• Automate deployment and scaling of ML models in production.
• Manage ML experimentation infrastructure on AWS, Azure, GCP.
• Monitor performance, health, and drift of deployed models.
• Collaborate with data scientists and engineers to operationalize ML solutions.
• Enforce version control, testing, and reproducibility in ML workflows.
• Troubleshoot ML infrastructure and deployment processes.
• Stay updated on MLOps tools and cloud computing trends.

Skills

Python

Go

Java

ML concepts

Automation scripting

Team collaboration

Education

Bachelor's or Master's degree in CS/Engineering

Tools

Docker

Kubernetes

MLflow

Kubeflow

Airflow

Job description

Placements24 is seeking a Senior AI/ML Operations (MLOps) Engineer in Soweto, Gauteng, to streamline the machine learning lifecycle from development to deployment and monitoring. You will build and maintain robust infrastructure and pipelines enabling data science teams to deliver reliable AI solutions.

You will design scalable MLOps pipelines, implement CI/CD for ML workflows, and automate deployment and scaling on cloud platforms like AWS, Azure, and GCP.