Senior AI/ML DevOps Engineer

Standard Bank Of South Africa Limited; Johannesburg; On-site; ZAR 900,000 - 1,300,000; Full time

Benefits offered by this job

Competitive salary

Annual performance incentives

Medical insurance

Retirement plan

Life insurance

Professional development

Collaborative work environment

AI initiatives in Sandton

Job summary

Standard Bank Of South Africa Limited is seeking an AI DevOps Engineer to build scalable AI/ML infrastructure and streamline the end-to-end ML lifecycle in Sandton. You will collaborate with data scientists and ML engineers to ensure automated and reliable MLOps workflows, covering data ingestion, model training, deployment, and monitoring.

The role emphasizes design and management of CI/CD pipelines, cloud-based deployments, and container orchestration with Docker and Kubernetes to scale AI

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in DevOps with a focus on AI/ML infrastructure.
• Proficiency with cloud platforms and containerization technologies.
• Experience with CI/CD tools (e.g., Jenkins, GitLab CI) and scripting languages (Python, Bash).
• Familiarity with MLOps principles and tools is highly desirable.

Responsibilities

• Design, implement, and maintain CI/CD pipelines for AI/ML models.
• Manage cloud infrastructure (AWS, Azure, GCP) supporting AI workloads.
• Implement containerization (Docker, Kubernetes) for model deployment and scaling.
• Develop and manage monitoring, logging, and alerting systems for AI applications.
• Automate infrastructure provisioning and management using infrastructure-as-code tools.

Skills

DevOps experience

AI/ML infra

Cloud platforms

Containerization

CI/CD tools

Scripting (Python, Bash)

Education

Bachelor's degree in Computer Science or Engineering

Tools

Docker

Kubernetes

Jenkins

GitLab CI

Job description

Standard Bank Of South Africa Limited is seeking an AI DevOps Engineer to build scalable AI/ML infrastructure and streamline the end-to-end ML lifecycle in Sandton. You will collaborate with data scientists and ML engineers to ensure automated and reliable MLOps workflows, covering data ingestion, model training, deployment, and monitoring.

The role emphasizes design and management of CI/CD pipelines, cloud-based deployments, and container orchestration with Docker and Kubernetes to scale AI