Machine Learning Operations (MLOps) Engineer

Placements24; Rustenburg; Híbrido; ZAR 600 000 - 1 100 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Competitive salary

Performance bonus

Medical aid

Pension/retirement contributions

Hybrid work model in Rustenburg

Training & conferences

Resumo da oferta

Placements24 is hiring an MLOps Engineer in Rustenburg, North West for a hybrid role bridging ML development and production deployment. You will design and maintain CI/CD pipelines, automate deployment and monitoring, and manage cloud-based ML infrastructure to ensure reliable, scalable operation.

You will collaborate with data scientists and software engineers, implement drift monitoring, and optimize workflows for cost and reliability.

Qualificações

• 3+ years of software engineering, DevOps, or MLOps experience with ML focus.
• Proven experience building and managing CI/CD pipelines for ML models.
• Proficiency in Python and cloud platforms.

Responsabilidades

• Design, implement, and manage CI/CD pipelines for ML models.
• Automate deployment, monitoring, and scaling of ML models in production.
• Develop and maintain infrastructure for data and model versioning.
• Implement monitoring for model performance, drift, and health.
• Collaborate with data scientists and software engineers for seamless deployment.
• Optimize ML workflows for efficiency and cost-effectiveness.
• Manage cloud-based ML infrastructure (AWS, Azure, GCP).
• Develop and maintain documentation for MLOps processes and tools.
• Troubleshoot ML deployment issues in production."],
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Conhecimentos

Python

CI/CD

Problem-solving

Communication

Formação académica

Bachelor's or Master's in CS/Engineering

Ferramentas

Docker

Kubernetes

Terraform

AWS

Azure

GCP

Descrição da oferta de emprego

About the Role

Our client is a rapidly growing AI startup focused on delivering innovative machine learning solutions. We are looking for a skilled Machine Learning Operations (MLOps) Engineer to join our team in Rustenburg, North West . This hybrid role is crucial for bridging the gap between machine learning development and reliable production deployment. You will be responsible for building and maintaining the infrastructure and workflows necessary to deploy, monitor, and manage machine learning models at scale. If you are passionate about streamlining ML pipelines and ensuring the operational excellence of AI systems, this is the role for you.

Key Responsibilities

• Design, implement, and manage CI/CD pipelines for machine learning models.
• Automate the deployment, monitoring, and scaling of ML models in production environments.
• Develop and maintain infrastructure for data and model versioning.
• Implement robust monitoring solutions for model performance, drift, and operational health.
• Collaborate with data scientists and software engineers to ensure seamless model deployment and integration.
• Optimize ML workflows for efficiency, reliability, and cost-effectiveness.
• Manage cloud-based ML infrastructure (e.g., AWS SageMaker, Azure ML, GCP AI Platform).
• Develop and maintain documentation for MLOps processes and tools.
• Troubleshoot and resolve issues related to ML model deployment and production performance.
• Stay up-to-date with the latest MLOps tools, technologies, and best practices.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in software engineering, DevOps, or MLOps, with a strong focus on machine learning.
• Proven experience building and managing CI/CD pipelines for ML models.
• Proficiency in programming languages such as Python.
• Experience with containerization technologies like Docker and orchestration tools like Kubernetes.
• Familiarity with cloud platforms (AWS, Azure, GCP) and their ML services.
• Understanding of machine learning concepts and workflows.
• Experience with infrastructure as code (IaC) tools (e.g., Terraform, CloudFormation).
• Strong problem-solving and debugging skills.
• Excellent communication and collaboration skills for a hybrid work environment.
• Knowledge of data pipelines and data management is beneficial.

Benefits

• We offer a competitive salary, performance bonuses, and a comprehensive benefits package including medical aid and retirement contributions.
• Our hybrid work model in Rustenburg supports work-life balance and team collaboration.
• Employees have access to excellent professional development opportunities, including training, workshops, and conferences.
• Join our client and be a key player in operationalizing cutting-edge machine learning technologies.
• Contribute to a dynamic team environment focused on innovation and growth.