Real-Time ML Engineer — AWS SageMaker & MLOps

Boardroom Appointments; Cape Town; On-site; ZAR 900,000 - 1,500,000; Full time

Job summary

Boardroom Appointments seeks an experienced ML Engineer to design, deploy, and optimize real-time ML models in AWS SageMaker and EKS. You will build CI/CD pipelines and ensure observability, reliability, and compliance in production environments.

You will collaborate with data scientists and engineers to align ML initiatives with business goals, automate retraining and monitoring, and take ownership of ML solutions across the stack.

Qualifications

• 5+ years in Machine Learning Engineering or ML platform roles.
• Strong Python, PySpark, SQL and ML libraries (TF/PyTorch/Scikit-learn).
• Hands-on experience with AWS ML services and MLOps tools.

Responsibilities

• Design, develop, and deploy ML models for real-time decisioning.
• Build and maintain CI/CD pipelines for ML deployments.
• Automate retraining, monitoring, and logging in production.
• Ensure regulatory and security compliance.
• Collaborate with data scientists and engineers to align ML with business needs.
• Own ML solutions and guide junior engineers.

Skills

Python

PySpark

SQL

TensorFlow

PyTorch

Scikit-learn

AWS SageMaker

AWS EKS

AWS Lambda

AWS Redshift

Terraform

Control-M

Docker

Kubernetes

GitHub Actions

OpenSearch

Prometheus

Grafana

CloudWatch

Tools

AWS SageMaker

AWS EKS

Lambda

Redshift

Terraform

Control-M

Docker

Kubernetes

GitHub Actions

OpenSearch

FluentBit

Kibana

Prometheus

Grafana

CloudWatch

Job description

Boardroom Appointments seeks an experienced ML Engineer to design, deploy, and optimize real-time ML models in AWS SageMaker and EKS. You will build CI/CD pipelines and ensure observability, reliability, and compliance in production environments.

You will collaborate with data scientists and engineers to align ML initiatives with business goals, automate retraining and monitoring, and take ownership of ML solutions across the stack.