Senior AI/ML Platform Engineer - Fully Remote

Placements24; Upington; Hybrid; ZAR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Health insurance

Paid time off

Professional development

AI resources access

Fully remote

Job summary

Placements24 is seeking a Senior AI/ML Platform Engineer to design, build, and maintain scalable AI/ML infrastructure remotely. You will manage MLOps pipelines, automate IaC, and optimize workflows across cloud platforms while collaborating with distributed data scientists and engineers.

The role requires deep expertise in cloud DevOps, containerization (Docker/Kubernetes), and MLOps tools (MLflow, Kubeflow, Seldon Core), with a strong focus on security and performance.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• 5+ years of experience in software engineering or DevOps with strong AI/ML platform focus.
• Proven experience building and managing cloud infrastructure (AWS, Azure or GCP).
• Strong expertise in containerization and orchestration (Docker, Kubernetes).
• Proficiency in Python, Bash, or Go.

Responsibilities

• Design, implement, and manage scalable AI/ML infra on cloud platforms (AWS/Azure/GCP).
• Develop and maintain MLOps pipelines for training, deployment, monitoring, versioning.
• Automate infrastructure provisioning and IaC tooling.
• Optimize AI/ML workflows for performance, cost, and scale.
• Collaborate with data scientists to understand needs and provide platform solutions.
• Ensure high availability and security of AI/ML platforms.

Skills

Cloud infrastructure

DevOps

AI/ML platforms

Containerization

CI/CD

Scripting

MLOps tools

Data storage

Remote collaboration

Education

Bachelor's or Master's degree in Computer Science

Tools

Docker

Kubernetes

MLflow

Kubeflow

Seldon Core

Jenkins

GitLab CI

Job description

Placements24 is seeking a Senior AI/ML Platform Engineer to design, build, and maintain scalable AI/ML infrastructure remotely. You will manage MLOps pipelines, automate IaC, and optimize workflows across cloud platforms while collaborating with distributed data scientists and engineers.

The role requires deep expertise in cloud DevOps, containerization (Docker/Kubernetes), and MLOps tools (MLflow, Kubeflow, Seldon Core), with a strong focus on security and performance.