Senior AI Platform Engineer — Fully Remote

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

Benefits offered by this job

Remote-first culture

Competitive salary

Health insurance

Professional development budget

Globally distributed teams

Job summary

Placements24 seeks a seasoned Senior AI Platform Engineer to join a remote-first, globally distributed engineering team. You will design, implement, and maintain scalable AI/ML platforms, enabling efficient AI development and research across time zones.

The role requires ownership of core platform components, building CI/CD pipelines for ML workflows, and integrating diverse tools. Strong cloud, Kubernetes, and MLOps experience are essential for success.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 5+ years of software engineering experience building and managing platforms, preferably for AI/ML.
• Proficiency with cloud environments (AWS, Azure, GCP) and container orchestration (Kubernetes).
• Experience with MLOps practices and tooling.
• Strong Python or Go programming skills.
• Excellent problem-solving skills and ability to work effectively in a remote team.

Responsibilities

• Design, develop, and manage scalable AI/ML platforms and infrastructure.
• Build and maintain CI/CD pipelines for ML workflows.
• Integrate AI/ML tools, libraries, and frameworks into a cohesive platform.
• Implement monitoring, logging, and alerting for platform health and performance.
• Provide robust support to data scientists and AI engineers using the platform.
• Automate infrastructure provisioning and management using infrastructure-as-code.

Skills

Python

Go

MLOps

Remote teamwork

Problem solving

Education

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

Tools

Kubernetes

Docker

CI/CD tooling

Job description

Placements24 seeks a seasoned Senior AI Platform Engineer to join a remote-first, globally distributed engineering team. You will design, implement, and maintain scalable AI/ML platforms, enabling efficient AI development and research across time zones.

The role requires ownership of core platform components, building CI/CD pipelines for ML workflows, and integrating diverse tools. Strong cloud, Kubernetes, and MLOps experience are essential for success.