Remote Lead ML Engineer, Cloud Platforms

Placements24; Kempton Park; Remote; ZAR 1,400,000 - 2,400,000; Full time

Benefits offered by this job

Remote-first culture

Professional development budget

Equipment stipend

Flexible time off

Job summary

Placements24 is seeking a Lead Machine Learning Engineer to spearhead the design, development, and deployment of production ML systems in a remote-first setup. You will architect scalable pipelines across cloud platforms and mentor a global team of engineers, translating research into robust, production-ready solutions.

The role requires a strong background in ML engineering, deep knowledge of MLOps, and proven leadership skills to drive strategic AI initiatives while collaborating with data

Qualifications

• Master's or PhD in CS/Engineering with ML specialization.
• 7+ years in ML engineering; 3+ years in lead role.
• Extensive production ML model deployment in cloud.
• Strong Python skills; TF, PyTorch, or scikit-learn.
• Experience with cloud ML services (SageMaker, Azure ML, Vertex AI).
• Deep knowledge of MLOps (Kubeflow, MLflow, Docker, Kubernetes).
• Proven remote-team leadership and collaboration.

Responsibilities

• Lead end-to-end ML systems design, development, and deployment.
• Architect scalable ML pipelines on AWS/Azure/GCP.
• Tune and deploy models for performance and efficiency.
• Collaborate with data scientists and software engineers.
• Enforce MLOps practices: CI/CD, monitoring, logging, versioning.
• Mentor a remote team of ML engineers.
• Evaluate new technologies to boost ML capabilities.
• Troubleshoot production ML issues.
• Contribute to AI strategy and roadmap.

Skills

Leadership

ML Engineer

Python

TensorFlow

PyTorch

Cloud Platforms

MLOps

Kubernetes

Education

Master's or PhD in CS or related

Tools

Kubeflow

MLflow

Docker

Kubernetes

SageMaker

Vertex AI

Job description

Placements24 is seeking a Lead Machine Learning Engineer to spearhead the design, development, and deployment of production ML systems in a remote-first setup. You will architect scalable pipelines across cloud platforms and mentor a global team of engineers, translating research into robust, production-ready solutions.

The role requires a strong background in ML engineering, deep knowledge of MLOps, and proven leadership skills to drive strategic AI initiatives while collaborating with data