Remote AI/ML Platform Engineer: Scale Impactful Infra

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

Benefits offered by this job

Competitive salary

Fully remote

AI infrastructure projects

Professional development budget

Access to cutting-edge technologies

Collaborative remote team culture

Impact on AI capabilities

Job summary

Placements24 is seeking an experienced AI/ML Platform Engineer for a fully remote role. You will design and maintain scalable AI/ML infrastructure, implement MLOps, and optimize cost and security across AWS, Azure, and GCP. Strong software, cloud, and IaC skills required.

You'll work with data scientists and ML engineers to streamline the ML lifecycle and enable rapid experimentation to production at scale, from anywhere in the world.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in software engineering, DevOps, or cloud infrastructure with a focus on ML platforms.
• Proficiency in Python, Go, or Java.

Responsibilities

• Design, build, and maintain scalable AI/ML infrastructure and platforms.
• Implement and manage MLOps best practices, including CI/CD, monitoring, and automation.
• Optimize infrastructure for performance, cost, and security.
• Develop tools and frameworks to streamline the ML lifecycle from experimentation to production.
• Collaborate with data scientists and ML engineers to understand infrastructure needs.
• Manage cloud resources and services (AWS, Azure, GCP) for AI/ML workloads.

Skills

Python

Go

Java

DevOps

Cloud infrastructure

Education

Bachelor's degree in CS/Engineering or related field

Tools

Docker

Kubernetes

MLflow

Kubeflow

Seldon

Terraform

Ansible

AWS

Azure

GCP

Job description

Placements24 is seeking an experienced AI/ML Platform Engineer for a fully remote role. You will design and maintain scalable AI/ML infrastructure, implement MLOps, and optimize cost and security across AWS, Azure, and GCP. Strong software, cloud, and IaC skills required.

You'll work with data scientists and ML engineers to streamline the ML lifecycle and enable rapid experimentation to production at scale, from anywhere in the world.