Senior AI MLOps Engineer - Remote, Equity & Growth

Placements24; Randburg; Hybrid; ZAR 900,000 - 1,500,000; Full time

Benefits offered by this job

Competitive salary and stock options

Job summary

Placements24 is seeking a Senior AI Engineer with a specialization in MLOps to join our fully remote team. You will design and maintain scalable ML pipelines, deploy models to production, and monitor performance across cloud environments.

You will collaborate with data scientists, implement IaC with Terraform, and build CI/CD pipelines for ML workflows. Strong Python, Docker, Kubernetes, and cloud experience are required.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
• 5+ years of experience in software engineering or DevOps, with a strong focus on MLOps or AI infrastructure.
• Proven experience building and managing end-to-end MLOps pipelines.
• Proficiency in at least one major cloud platform (AWS, Azure, GCP) and their ML services.
• Strong experience with Docker and Kubernetes.
• Experience with CI/CD tools (Jenkins, GitLab CI, GitHub Actions).
• Proficiency in Python and shell scripting.
• Terraform or similar IaC tools.

Responsibilities

• Design, build, and maintain scalable MLOps pipelines for model development, training, deployment, and monitoring.
• Implement IaC solutions for cloud-based ML environments (e.g., Terraform, Ansible).
• Develop and manage CI/CD pipelines for ML workflows.
• Set up monitoring and alerting for production ML models, tracking drift and performance.
• Automate model retraining and deployment processes.
• Collaborate with data scientists to optimize models for production.
• Containerize ML apps with Docker and orchestrate with Kubernetes.
• Ensure security best practices across MLOps infrastructure.
• Troubleshoot ML system performance and reliability.

Job description

Placements24 is seeking a Senior AI Engineer with a specialization in MLOps to join our fully remote team. You will design and maintain scalable ML pipelines, deploy models to production, and monitor performance across cloud environments.

You will collaborate with data scientists, implement IaC with Terraform, and build CI/CD pipelines for ML workflows. Strong Python, Docker, Kubernetes, and cloud experience are required.