Converter Operator

Freudenberg Nonwovens; Cape Town; Remote; ZAR 600,000 - 1,200,000; Full time

Benefits offered by this job

Remote-friendly salary

Fully remote with flexible hours

Health benefits

Paid time off

Learning & development

Job summary

Freudenberg Nonwovens is seeking a Remote Machine Learning Operations Engineer (MLOps) to join our distributed technology team. You will build and maintain the ML infrastructure across experimentation to production, ensuring reliability at scale.

Work remotely with data scientists and software engineers to streamline deployment and operationalization of ML models in cloud environments, implementing robust CI/CD pipelines and scalable ML workflows.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field; Master’s preferred.
• 3–5 years in MLOps, DevOps, or SRE with ML focus.
• Proficiency in Python and scripting; cloud platforms experience.
• Strong containerization knowledge with Docker and Kubernetes.
• Experience with ML frameworks and data pipelines; CI/CD familiarity.

Responsibilities

• Design, build, and maintain robust CI/CD pipelines for ML models.
• Manage infrastructure for training, deployment, and serving on cloud platforms.
• Develop monitoring for ML performance, drift, and health.
• Collaborate with data scientists to optimize production-ready models.
• Implement version control for data, code, and models.
• Troubleshoot ML system performance and reliability issues.

Skills

MLOps experience

DevOps experience

Python proficiency

Scripting languages

CI/CD knowledge

Data pipelines

Monitoring tools

Cloud platforms (AWS/GCP/Azure)

Education

Bachelor's degree in CS/Engineering

Master's degree preferred

Tools

Docker

Kubernetes

TensorFlow

PyTorch

Scikit-learn

Job description

Remote Machine Learning Operations Engineer (MLOps)

Our client is seeking a highly skilled Remote Machine Learning Operations Engineer (MLOps) to join their innovative, distributed technology team. This role is essential for building and maintaining the infrastructure and pipelines that support the machine learning lifecycle, from experimentation to production deployment and monitoring. You will ensure the reliability, scalability, and efficiency of our ML systems. Working remotely, you will collaborate with data scientists and software engineers to streamline the deployment and operationalization of ML models across various cloud environments.

About the Role

Our client is seeking a highly skilled Remote Machine Learning Operations Engineer (MLOps) to join their innovative, distributed technology team. This role is essential for building and maintaining the infrastructure and pipelines that support the machine learning lifecycle, from experimentation to production deployment and monitoring. You will ensure the reliability, scalability, and efficiency of our ML systems. Working remotely, you will collaborate with data scientists and software engineers to streamline the deployment and operationalization of ML models across various cloud environments.

Key Responsibilities

• Design, build, and maintain robust CI/CD pipelines for machine learning models.
• Implement and manage infrastructure for ML model training, deployment, and serving, leveraging cloud platforms.
• Develop and automate monitoring systems for ML model performance, drift, and system health.
• Collaborate with data scientists to optimize models for production readiness and scalability.
• Implement version control strategies for data, code, and models.
• Troubleshoot and resolve issues related to ML system performance and reliability.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field; Master's preferred.
• 3-5 years of experience in MLOps, DevOps, or site reliability engineering with a focus on ML.
• Proficiency in Python and scripting languages, with experience in cloud platforms (AWS, Azure, GCP).
• Strong understanding of containerization technologies (Docker, Kubernetes).
• Experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Familiarity with data pipelines, monitoring tools, and CI/CD principles.

Benefits

• Competitive salary tailored for remote roles.
• Fully remote work arrangement with flexible hours.
• Comprehensive health, dental, and vision benefits.
• Generous paid time off and annual leave.
• Opportunities for continuous learning and professional development in cutting-edge MLOps practices.