MLOps Engineer

Placements24; Polokwane; Hybrid; ZAR 700,000 - 1,200,000; Full time

Benefits offered by this job

Hybrid work model

Competitive salary

Professional development opportunities

Job summary

Placements24 seeks a skilled MLOps Engineer in Polokwane to advance their ML production. You will build CI/CD pipelines, manage training and serving infra, and monitor models in production.

The ideal candidate has strong MLOps/SRE background, Python, Docker/Kubernetes, and cloud experience (AWS/Azure/GCP). This hybrid role offers exposure to cutting‑edge ML tooling.

Qualifications

• Bachelor's degree in CS/Engineering or related field.
• Experience in MLOps, DevOps or SRE roles.
• Strong ML lifecycle understanding.
• Proficiency in Python, Bash and cloud platforms (AWS/Azure/GCP).
• Experience with Docker, Kubernetes, Terraform and Ansible.
• Familiarity with ML frameworks (TensorFlow, PyTorch, scikit-learn) and deployment.

Responsibilities

• Design, build, and maintain scalable CI/CD pipelines for ML models.
• Manage infrastructure for training, deployment, and serving.
• Develop monitoring for model performance and data drift.
• Automate ML workflows from data ingestion to validation.
• Collaborate with data scientists and software engineers for deployment.

Skills

MLOps

DevOps

SRE

Python

TensorFlow

PyTorch

scikit-learn

CI/CD

Docker

Kubernetes

Cloud (AWS/Azure/GCP)

Education

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

Tools

Terraform

Ansible

Job description

About the Role

Our client is seeking a skilled MLOps Engineer to enhance their machine learning operational capabilities in Polokwane. This role is crucial for bridging the gap between machine learning model development and reliable, scalable production deployment. You will be responsible for building and maintaining the infrastructure, tools, and processes that enable the continuous integration, delivery, and monitoring of machine learning models. This position offers a great opportunity to work with cutting-edge technologies and play a vital role in streamlining the ML lifecycle, ensuring efficient and effective delivery of AI-powered features.

Key Responsibilities

• Design, build, and maintain scalable CI/CD pipelines for machine learning models.
• Implement and manage infrastructure for model training, deployment, and serving, often using containerization technologies (Docker, Kubernetes).
• Develop monitoring solutions to track model performance, data drift, and system health in production.
• Automate ML workflows, including data ingestion, feature engineering, model training, and validation.
• Collaborate closely with data scientists and software engineers to ensure smooth model deployment and lifecycle management.
• Troubleshoot and resolve issues related to ML infrastructure and model performance.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Proven experience in MLOps, DevOps, or Site Reliability Engineering (SRE) roles.
• Strong understanding of machine learning concepts and the ML lifecycle.
• Proficiency in scripting languages (e.g., Python, Bash) and cloud platforms (AWS, Azure, GCP).
• Experience with containerization tools (Docker, Kubernetes) and infrastructure as code (Terraform, Ansible).
• Familiarity with ML frameworks (TensorFlow, PyTorch, scikit-learn) and model deployment strategies.

Benefits

• Competitive salary and comprehensive benefits.
• Hybrid work model offering flexibility.
• Opportunities to work with advanced MLOps tools and methodologies.
• Professional development and training programs.
• Contribution to impactful AI projects within a collaborative team.
• A culture that fosters innovation and technical excellence.