Senior AI Engineer — MLOps & Deployment Lead (Hybrid)

Placements24; Noord-Kaap; Hybrid; ZAR 1,000,000 - 1,500,000; Full time

Benefits offered by this job

Hybrid work model

Competitive salary

Professional growth

Job summary

Placements24 in Kimberley, South Africa, invites a Senior AI Engineer specializing in MLOps to join our client in a hybrid role. You will streamline AI development lifecycle, deploy, monitor, and scale ML models while collaborating with data scientists and software engineers.

The ideal candidate has 5+ years in software/DevOps with MLOps focus, strong Python, Docker, Kubernetes, and cloud ML services; enjoy working in a dynamic, innovative environment.

Qualifications

• 5+ years of software engineering or DevOps with a focus on MLOps.
• Proven experience building CI/CD pipelines for ML models.
• Strong cloud experience (AWS, Azure, or GCP) with ML services.
• Proficient in Python and ML frameworks like TensorFlow or PyTorch.

Responsibilities

• Design and maintain scalable MLOps pipelines for training, deployment, monitoring, and retraining.
• Automate the ML lifecycle end-to-end using CI/CD best practices.
• Manage infrastructure for ML model serving with high availability and low latency.
• Implement monitoring and alerting for ML models in production.
• Collaborate with data scientists to optimize models for production deployment.
• Oversee containerization and orchestration of ML workloads (Docker/Kubernetes).
• Ensure security and compliance of ML systems and data.
• Troubleshoot deployment and performance issues in ML models.
• Stay current with MLOps tools, technologies, and best practices.

Skills

MLOps

CI/CD pipelines

Python

Docker

Kubernetes

Cloud platforms

TensorFlow

PyTorch

Scikit-learn

Monitoring

Education

Bachelor's degree in CS/Engineering

Master's degree preferred

Tools

Docker

Kubernetes

Cloud ML services

CI/CD tooling

Job description

Placements24 in Kimberley, South Africa, invites a Senior AI Engineer specializing in MLOps to join our client in a hybrid role. You will streamline AI development lifecycle, deploy, monitor, and scale ML models while collaborating with data scientists and software engineers.

The ideal candidate has 5+ years in software/DevOps with MLOps focus, strong Python, Docker, Kubernetes, and cloud ML services; enjoy working in a dynamic, innovative environment.