Machine Learning Engineer

Cloud23; Johannesburg; On-site; ZAR 700,000 - 1,100,000; Full time

Job summary

Cloud23 is seeking a software engineer to turn research models into scalable, production-ready services. You’ll package, serve, scale, and version models to run reliably in real traffic.

You’ll build evaluation and monitoring that signals drift or failure. Design for latency budgets, fallback behavior, and correctness when models are wrong, all within security and data residency constraints.

Qualifications

• Strong software engineering fundamentals; code maintainable.
• Experience deploying ML systems that real users depend on.
• Comfort with containers, CI/CD and cloud infrastructure (AWS preferred).
• Understanding of model evaluation beyond a single accuracy number.
• Experience in a regulated environment is valued.

Responsibilities

• Take models from experiment to production service — packaging, serving, scaling and versioning them.
• Build the evaluation and monitoring that tells you a model has quietly stopped working.
• Engineer for the failure cases: latency budgets, fallback behaviour, and what happens when the model is wrong.
• Work inside enterprise constraints — security review, change control, data residency — without losing velocity.
• Review the work of others and raise the engineering standard around you.

Skills

Software engineering fundamentals

ML system deployment

Containers & CI/CD

Cloud infrastructure (AWS)

Model evaluation beyond accuracy

Regulated environment experience

Tools

Docker

Kubernetes

CI/CD

AWS

Job description

Turn research models into scalable, production-ready systems that survive real traffic, real data drift and real audit.

What you’ll do

• Take models from experiment to production service — packaging, serving, scaling and versioning them.
• Build the evaluation and monitoring that tells you a model has quietly stopped working.
• Engineer for the failure cases: latency budgets, fallback behaviour, and what happens when the model is wrong.
• Work inside enterprise constraints — security review, change control, data residency — without losing velocity.
• Review the work of others and raise the engineering standard around you.

What we’re looking for

• Strong software engineering fundamentals; you write code others can maintain.
• Experience deploying ML systems that real users depend on.
• Comfort with containers, CI/CD and cloud infrastructure (AWS preferred).
• Understanding of model evaluation beyond a single accuracy number.
• Experience in a regulated environment is valued.