Remote Lead AI Engineer — MLOps & Production ML

Placements24; Stellenbosch; Hybrid; ZAR 1,200,000 - 2,000,000; Full time

Benefits offered by this job

Fully remote

Competitive compensation

Career growth opportunities

Job summary

Placements24 seeks an experienced Remote Lead AI Engineer with a specialization in MLOps to drive innovation within its AI & Emerging Technologies team. This fully remote role lets you lead and mentor a team while building and scaling automated ML pipelines for production deployment from any location.

You will deploy, monitor, and manage AI models, partnering with data scientists and software engineers to optimize the ML lifecycle with automation and best practices across cloud platforms,

Qualifications

• Must have 5+ years in software engineering/DevOps with a strong MLOps focus in recent years.
• Proven experience building and managing CI/CD pipelines for ML models.
• Strong understanding of cloud ML services and containerization.

Responsibilities

• Lead design and implementation of MLOps strategies and infra.
• Build and maintain automated ML CI/CD pipelines.
• Develop robust monitoring and logging for AI/ML apps.
• Manage model versioning, testing, and deployment processes.
• Mentor junior engineers on the MLOps team.
• Collaborate with data scientists and software engineers to optimize ML lifecycle.

Skills

MLOps

CI/CD

Python

Cloud platforms (AWS/Azure/GCP)

Docker/Kubernetes

Monitoring & logging

Education

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

Tools

Jenkins

GitLab CI

GitHub Actions

Job description

Placements24 seeks an experienced Remote Lead AI Engineer with a specialization in MLOps to drive innovation within its AI & Emerging Technologies team. This fully remote role lets you lead and mentor a team while building and scaling automated ML pipelines for production deployment from any location.

You will deploy, monitor, and manage AI models, partnering with data scientists and software engineers to optimize the ML lifecycle with automation and best practices across cloud platforms,