Senior ML Operations (MLOps) Engineer

Placements24; Stellenbosch; On-site; ZAR 900,000 - 1,500,000; Full time

Benefits offered by this job

Relocation assistance

Health & retirement benefits

Training & certifications in MLOps

Job summary

Placements24 is seeking a Senior MLOps Engineer to join a leading AI analytics platform team in Paarl, Western Cape. You will bridge model development and production deployment, building robust MLOps pipelines and automating ML workflows to ensure CI/CD, delivery, and monitoring of models.

The role requires 5+ years in software/DevOps with at least 2 years in MLOps, strong cloud and containerization experience, Python scripting, and proficiency with ML frameworks.

Qualifications

• 5+ years of software engineering or DevOps experience.
• 2+ years focused on MLOps.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Proficiency in Python scripting.
• Experience with CI/CD tools (Jenkins, GitLab CI, GitHub Actions).
• Familiarity with ML frameworks (TensorFlow, PyTorch, scikit-learn) and ML lifecycle concepts.
• Understanding of monitoring, logging, and model versioning.

Responsibilities

• Design, implement, and manage CI/CD pipelines for ML models.
• Automate deployment, scaling, and monitoring of ML models.
• Develop infrastructure for ML experimentation, training, and inference.
• Implement tools for model versioning, reproducibility, and lineage tracking.
• Monitor performance and drift; plan retraining and updates.
• Collaborate with data scientists to streamline the ML lifecycle.
• Ensure reliability, scalability, and security of MLOps infra.
• Apply data governance and model validation best practices.
• Troubleshoot deployment and performance issues.
• Stay updated with emerging MLOps tools and practices.

Skills

5+ years SWE/DevOps

2+ years MLOps

Cloud platforms

Python

CI/CD tooling

ML frameworks

Education

Bachelor's degree in CS/Engineering

Master's degree preferred

Tools

Docker

Kubernetes

Jenkins

GitLab CI

GitHub Actions

TensorFlow

PyTorch

scikit-learn

Job description

About the Role

Our client, a leader in developing AI-driven analytics platforms, is seeking a Senior MLOps Engineer to join their dedicated team in Paarl, Western Cape . This role is critical for bridging the gap between machine learning model development and reliable, scalable production deployment. You will be responsible for building and maintaining robust MLOps pipelines, automating ML workflows, and ensuring the continuous integration, delivery, and monitoring of machine learning models. The ideal candidate has a strong background in software engineering, DevOps practices, and a deep understanding of the machine learning lifecycle. This position offers the chance to work with state-of-the-art technologies in a collaborative environment within the picturesque setting of Paarl .

Key Responsibilities

• Design, implement, and manage CI/CD pipelines for machine learning models.
• Automate the deployment, scaling, and monitoring of ML models in production environments.
• Develop and maintain infrastructure for ML experimentation, training, and inference.
• Implement tools and practices for model versioning, reproducibility, and lineage tracking.
• Monitor model performance and drift in production, and implement strategies for retraining and updates.
• Collaborate closely with data scientists and ML engineers to streamline the ML lifecycle.
• Ensure the reliability, scalability, and security of MLOps infrastructure.
• Implement best practices for data governance and model validation.
• Troubleshoot and resolve issues related to ML model deployment and performance.
• Stay current with emerging MLOps tools, technologies, and best practices.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
• 5+ years of experience in software engineering or DevOps, with at least 2 years focused on MLOps.
• Strong experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Proficiency in scripting languages such as Python.
• Experience with CI/CD tools (e.g., Jenkins, GitLab CI, GitHub Actions).
• Familiarity with ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and ML platforms.
• Understanding of machine learning concepts and the ML development lifecycle.
• Experience with monitoring and logging tools.
• Excellent problem-solving and troubleshooting skills.
• Strong communication and collaboration abilities.

Benefits

• Competitive salary and annual performance bonus.
• Comprehensive health, disability, and retirement benefits.
• Opportunities for advanced training and certifications in MLOps and cloud technologies.
• Supportive and collaborative team environment.
• Generous paid time off.
• Access to cutting-edge MLOps tooling and infrastructure.
• Relocation assistance for candidates relocating to Paarl, Western Cape .