Hybrid AI Systems & MLOps Engineer

Placements24; Mbombela (Nelspruit); Hybrid; ZAR 700,000 - 1,200,000; Full time

Benefits offered by this job

Hybrid work flexibility

Professional development and training

Pension fund

Job summary

Placements24 is seeking an experienced AI Systems Engineer in Nelspruit to design, build, and maintain robust AI infrastructure and MLOps pipelines. The role supports data scientists and researchers through scalable, reliable cloud-based services in a hybrid work environment.

The ideal candidate has a strong background in systems engineering, cloud computing, and AI/ML workflows, collaborating with cross-functional teams to accelerate AI innovation and optimize performance.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field.
• Proven experience in systems engineering, DevOps or MLOps.
• Strong knowledge of cloud platforms (AWS, Azure, or GCP).
• Experience with Docker and Kubernetes.
• Familiar with CI/CD pipelines and tools.
• Proficiency in Python or Bash.
• Excellent problem-solving and teamwork skills.
• Hybrid work setup experience is a plus.

Responsibilities

• Design, build, and maintain scalable AI infra and MLOps pipelines.
• Manage cloud-based AI services (SageMaker, Azure ML, GCP).
• Develop and automate ML deployment processes.
• Monitor performance, identify bottlenecks, optimize.
• Ensure security, reliability, availability of AI systems.
• Collaborate with data scientists and engineers on infra needs.
• Troubleshoot AI systems and platforms.
• Manage Docker and Kubernetes orchestration.
• Document architecture, configurations, operations.
• Stay updated on AI infra trends.

Skills

Systems engineering

DevOps

MLOps

Cloud computing

Python

CI/CD

Troubleshooting

Communication

Teamwork

Hybrid work

Education

Bachelor's degree in Computer Science or Engineering

Tools

Docker

Kubernetes

AWS

Azure

GCP

Job description

Placements24 is seeking an experienced AI Systems Engineer in Nelspruit to design, build, and maintain robust AI infrastructure and MLOps pipelines. The role supports data scientists and researchers through scalable, reliable cloud-based services in a hybrid work environment.

The ideal candidate has a strong background in systems engineering, cloud computing, and AI/ML workflows, collaborating with cross-functional teams to accelerate AI innovation and optimize performance.