AI Platform Engineer — Scalable ML Infra & Pipelines

Bash; Cape Town; Sur place; ZAR 900 000 - 1 300 000; Plein temps

Avantages offerts par ce poste

Competitive salary & bonus

Health benefits

Paid time off

Growth opportunities

Résumé du poste

AECOM in Kimberley is seeking an AI Platform Engineer to build, scale, and maintain the infrastructure for AI and ML initiatives. You will develop robust data pipelines, manage ML workflows, and ensure reliable deployment environments, enabling cutting-edge AI capabilities.

Join a collaborative, innovative team and work with Kubeflow, MLflow, Docker, Kubernetes, and major cloud platforms to support data scientists and ML engineers in delivering impactful solutions.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related technical field.
• 3+ years of experience in platform engineering, DevOps, or MLOps.
• Proficiency with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Experience with infrastructure as code tools (Terraform, Ansible).
• Familiarity with data processing frameworks (Spark, Flink) and ML libraries.

Responsabilités

• Design, build, and maintain scalable AI/ML infrastructure and platforms.
• Develop and optimize data pipelines for ingestion, processing, and storage of large datasets.
• Implement and manage ML workflow orchestration tools (Kubeflow, MLflow).
• Ensure the performance, reliability, and security of AI development and production environments.
• Collaborate with data scientists and ML engineers to support their operational needs.

Formation

Bachelor's degree in Computer Science, Engineering, or related technical field

Outils

AWS

Azure

GCP

Docker

Kubernetes

Terraform

Ansible

Spark

Flink

Description du poste

AECOM in Kimberley is seeking an AI Platform Engineer to build, scale, and maintain the infrastructure for AI and ML initiatives. You will develop robust data pipelines, manage ML workflows, and ensure reliable deployment environments, enabling cutting-edge AI capabilities.

Join a collaborative, innovative team and work with Kubeflow, MLflow, Docker, Kubernetes, and major cloud platforms to support data scientists and ML engineers in delivering impactful solutions.