MLOps Engineer: Build & Scale AI Pipelines (On-Site)

Placements24; Polokwane; On-site; ZAR 600,000 - 900,000; Full time

Benefits offered by this job

Health insurance

Retirement contributions

Career advancement

Performance-based incentives

Modern facilities

Job summary

Placements24 seeks an experienced MLOps Engineer to join our Polokwane team on-site. You will design scalable ML pipelines, implement end-to-end CI/CD for models, and ensure monitoring, retraining, and secure deployment of AI solutions in production.

Collaborate with data scientists and software engineers to operationalize ML models, drive reliability, and optimize cloud infrastructure across AWS/Azure/GCP. The role offers growth in a fast-paced AI-focused environment in Limpopo.

Qualifications

• Bachelor's degree in CS/Engineering or related quantitative field.
• Proven experience in MLOps, DevOps or ML-focused software engineering.
• Strong Python programming skills and scripting ability.
• Experience with cloud platforms (AWS/Azure/GCP) and containerization (Docker/Kubernetes).
• Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience with CI/CD tools (Jenkins, GitHub Actions, GitLab CI).
• Understanding of ML lifecycle management and model monitoring.

Responsibilities

• Design and manage scalable ML pipelines for training, validation and deployment.
• Build and maintain CI/CD processes for ML models.
• Implement monitoring to detect drift and performance issues in production.
• Automate model retraining and deployment workflows.
• Collaborate with data scientists and software engineers to operationalize models.

Skills

Python programming

MLOps

DevOps

ML model deployment

Problem solving

Independent worker

Team collaboration

Education

Bachelor's degree in Computer Science or Engineering

Tools

Docker

Kubernetes

AWS

Azure

GCP

Kubeflow

MLflow

Job description

Placements24 seeks an experienced MLOps Engineer to join our Polokwane team on-site. You will design scalable ML pipelines, implement end-to-end CI/CD for models, and ensure monitoring, retraining, and secure deployment of AI solutions in production.

Collaborate with data scientists and software engineers to operationalize ML models, drive reliability, and optimize cloud infrastructure across AWS/Azure/GCP. The role offers growth in a fast-paced AI-focused environment in Limpopo.