Remote MLOps Engineer - Scale ML Pipelines & Infra

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

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Retirement plan

Paid time off

Professional development budget

Remote work

Job summary

Placements24 is seeking a Senior MLOps Engineer to design, deploy, and monitor scalable ML infrastructure in a fully remote setup. You will bridge data science and IT operations to ensure robust ML model deployment and operational excellence across cloud platforms.

The role requires a strong software engineering background, expertise in MLOps, and hands-on experience with AWS/Azure/GCP, Docker/Kubernetes, and IaC tools. Join a fast-paced team driving AI-driven analytics remotely.

Qualifications

• BS in Computer Science, Engineering or related field; MS a plus.
• 5+ years in software engineering/DevOps, with ≥3 years in MLOps or ML cloud infra.
• Proficiency in Python; Bash scripting experience.
• Hands-on with cloud platforms (AWS/Azure/GCP) and ML services.

Responsibilities

• Design and manage CI/CD pipelines for ML models.
• Build and maintain scalable ML training, deployment, and serving infra.
• Implement monitoring, logging and alerting for ML in production.
• Automate ML lifecycle: data validation, training, testing, deployment.
• Collaborate with data scientists and engineers to streamline ML workflows.
• Ensure reliability, scalability, and security of ML systems and infra.
• Optimize cloud resources for ML workloads; troubleshoot issues.
• Stay current with emerging MLOps tools and best practices.

Skills

Python

Shell scripting

Cloud platforms

Docker/Kubernetes

CI/CD tools

IaC (Terraform/Ansible)

ML frameworks

Communication & problem solving

Education

Bachelor's in CS/Engineering

Master's degree preferred

Tools

Docker

Kubernetes

Terraform

Ansible

GitHub Actions

Jenkins

Job description

Placements24 is seeking a Senior MLOps Engineer to design, deploy, and monitor scalable ML infrastructure in a fully remote setup. You will bridge data science and IT operations to ensure robust ML model deployment and operational excellence across cloud platforms.

The role requires a strong software engineering background, expertise in MLOps, and hands-on experience with AWS/Azure/GCP, Docker/Kubernetes, and IaC tools. Join a fast-paced team driving AI-driven analytics remotely.