Senior MLOps Engineer — AI Lifecycle & Deployment (Hybrid)

Placements24; Sandton; Hybrid; ZAR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Performance bonuses

Career advancement

Training, certifications, and конферен

Health, dental, and vision insurance

Retirement savings plan

Ample paid time off

Job summary

Placements24 in Sandton, Gauteng, is seeking a Senior Machine Learning Engineer with a strong MLOps focus. You will design and maintain scalable ML pipelines, deploy models, and ensure reliability in production within a hybrid work setup.

You will collaborate with data scientists and software engineers, implementing CI/CD, monitoring, and retraining processes. A deep understanding of ML and software engineering best practices is required.

Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, or related field.
• Minimum 5 years in software or ML engineering, with ≥2 years in MLOps.
• Experience building ML pipelines with Kubeflow, MLflow, or SageMaker.
• Proficient in Python and ML frameworks such as TensorFlow or PyTorch.
• Experience with cloud platforms and container orchestration (Kubernetes).

Responsibilities

• Design, build, and maintain scalable MLOps pipelines for model training and deployment.
• Implement CI/CD practices for ML models and updates.
• Develop infrastructure for ML systems on AWS/Azure/GCP; use Docker/Kubernetes.
• Monitor drift, performance, and health; set up alerts and rollbacks.
• Collaborate with data scientists and engineers to productionize models.
• Optimize ML workflows for cost, speed, and reliability.
• Create tools to manage and operationalize ML models securely.

Skills

MLOps

Python

Cloud (AWS/Azure/GCP)

CI/CD

Git

System design

Communication

Education

Bachelor's or Master's in Computer Science / Software Engineering

Tools

Kubeflow

MLflow

SageMaker

Docker

Kubernetes

TensorFlow

PyTorch

Job description

Placements24 in Sandton, Gauteng, is seeking a Senior Machine Learning Engineer with a strong MLOps focus. You will design and maintain scalable ML pipelines, deploy models, and ensure reliability in production within a hybrid work setup.

You will collaborate with data scientists and software engineers, implementing CI/CD, monitoring, and retraining processes. A deep understanding of ML and software engineering best practices is required.