Remote Machine Learning Operations Engineer (MLOps)

Placements24; LegKraal Gate; Hybrid; ZAR 600,000 - 1,000,000; Full time

Benefits offered by this job

Fully remote work

Flexible hours

Health benefits

Professional development

Job summary

Placements24 is seeking a highly skilled Remote Machine Learning Operations Engineer (MLOps) to join its distributed technology team. You will build and maintain infrastructure and pipelines supporting the ML lifecycle, from experimentation to production deployment and monitoring.

As part of a remote team, you will collaborate with data scientists and software engineers to streamline deployment and operations of ML models across cloud environments.

Qualifications

• Bachelor's degree in Computer Science or related field; master's preferred.
• 3-5 years in MLOps/DevOps with ML focus.
• Proficiency in Python and scripting; cloud experience (AWS/Azure/GCP).
• Experience with containers and orchestration (Docker, Kubernetes).
• Familiarity with ML frameworks (TensorFlow, PyTorch).
• Knowledge of data pipelines and CI/CD principles.

Responsibilities

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

Skills

Python

Scripting

CI/CD

Cloud platforms

Data pipelines

Monitoring

Education

Bachelor's degree in Computer Science

Master's preferred

Tools

Docker

Kubernetes

TensorFlow

PyTorch

Scikit-learn

Job description

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.