Senior AI Engineer — Remote-Friendly, Equity & Growth

Placements24; Gauteng; Hybrid; ZAR 900,000 - 1,600,000; Full time

Benefits offered by this job

Competitive salary

Medical, dental, vision coverage

Stock options

Professional development opportunities

Remote-friendly environment

Job summary

Placements24 in South Africa is seeking a Senior AI Engineer to join their tech team in Gauteng. You will design, develop, and deploy scalable AI systems addressing business challenges, collaborating with data scientists and engineers to bring AI capabilities to life.

You will work on production-ready models, ML pipelines, MLOps practices, and cloud deployments, ensuring performance, reliability, and scalability in a fast-growing environment.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• 5+ years of professional experience in software engineering with a focus on AI/ML.
• Strong programming skills in Python, Java or Scala and ML libraries.

Responsibilities

• Design, build, and maintain robust and scalable AI/ML pipelines and infrastructure.
• Develop and implement production-ready AI models for predictive analytics, recommendations, and automation.
• Optimize AI algorithms for efficiency, accuracy, and scalability.
• Collaborate with data scientists to translate research models into deployable software.
• Implement MLOps practices for model deployment, monitoring, and management in cloud environments.
• Troubleshoot and resolve issues in AI systems to ensure reliable operation.

Skills

Python

Java

Scala

MLOps

Education

Bachelor's or Master's degree in Computer Science, Engineering, or related field

Tools

TensorFlow

PyTorch

Scikit-learn

AWS

Azure

GCP

Docker

Kubernetes

Job description

Placements24 in South Africa is seeking a Senior AI Engineer to join their tech team in Gauteng. You will design, develop, and deploy scalable AI systems addressing business challenges, collaborating with data scientists and engineers to bring AI capabilities to life.

You will work on production-ready models, ML pipelines, MLOps practices, and cloud deployments, ensuring performance, reliability, and scalability in a fast-growing environment.