Remote Lead ML Engineer for Scalable AI Pipelines

Placements24; Gauteng; Hybrid; ZAR 1,500,000 - 2,500,000; Full time

Benefits offered by this job

Health insurance

Remote-first culture

Paid time off

Professional development budget

Equipment stipend

Job summary

Placements24 is seeking a Lead Machine Learning Engineer to architect and deploy scalable ML systems in a remote-first environment. You will guide a team of engineers, drive MLOps practices, and align ML initiatives with strategic goals across cloud platforms.

The role requires a strong technical background in ML, cloud services (AWS/Azure/GCP), and leadership capabilities for a distributed team.

Qualifications

• Master's degree or PhD in Computer Science, Engineering, or a related field with ML specialization.
• Minimum 7 years in ML engineering, at least 3 in lead/senior roles.
• Experience deploying ML models in production in cloud settings.
• Expertise in Python and ML frameworks (TF, PyTorch, scikit-learn).

Responsibilities

• Lead design, development, and deployment of end-to-end ML systems and infrastructure.
• Architect scalable, production-ready ML pipelines on cloud platforms.
• Oversee model selection, tuning, and deployment for performance.
• Collaborate with data scientists and engineers to translate research into deployable products.
• Establish MLOps practices: CI/CD, monitoring, logging, versioning for ML models/data.
• Mentor a remote team of ML engineers.

Skills

Python

TensorFlow

PyTorch

scikit-learn

Cloud platforms

MLOps

Kubeflow

MLflow

Docker

Kubernetes

SageMaker

Vertex AI

Big data Spark

Education

Master's degree in CS/Engineering

PhD in ML or related

Tools

AWS

Azure

GCP

Job description

Placements24 is seeking a Lead Machine Learning Engineer to architect and deploy scalable ML systems in a remote-first environment. You will guide a team of engineers, drive MLOps practices, and align ML initiatives with strategic goals across cloud platforms.

The role requires a strong technical background in ML, cloud services (AWS/Azure/GCP), and leadership capabilities for a distributed team.