AI/ML Operations (MLOps) Engineer

Placements24; United States; Hybrid; USD 36,000 - 73,000; Full time

Job summary

Placements24 is seeking an AI/ML Operations (MLOps) Engineer to join a collaborative team in Paarl, Western Cape. The role focuses on deploying, monitoring, and managing ML models in production, bridging data science, software engineering, and DevOps.

Hybrid work model combines office collaboration with remote flexibility. The ideal candidate has 3+ years in DevOps, SRE, or MLOps, with hands-on experience in MLflow, Kubeflow, and Airflow, plus Python, Docker, and Kubernetes.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, or a related technical field.

Responsibilities

• Design, build, and maintain CI/CD pipelines for ML models.
• Implement and manage infrastructure for model training, deployment, and serving.
• Develop and automate monitoring for model performance and health.
• Collaborate with data scientists and engineers to transition from dev to prod.
• Containerize apps with Docker and orchestrate with Kubernetes.
• Apply IaC using Terraform or Ansible.
• Manage cloud ML services (AWS, Azure, GCP).
• Troubleshoot production ML deployment issues.

Skills

CI/CD pipelines

MLOps

Python scripting

Docker

Education

Bachelor's degree in Computer Science or related field

Tools

MLflow

Kubeflow

Airflow

Terraform

Job description

About the Role

Our client, a prominent force in the AI & Emerging Technologies sector, is seeking a skilled AI/ML Operations (MLOps) Engineer to join their collaborative team in Paarl, Western Cape. This role is vital for ensuring the seamless deployment, monitoring, and management of machine learning models in production environments. You will work at the intersection of data science, software engineering, and DevOps, implementing best practices to streamline the ML lifecycle. This position offers a Hybrid work model, balancing office collaboration with remote flexibility. Join a company that is revolutionizing industries through AI and contribute to its operational excellence.

Key Responsibilities

• Design, build, and maintain robust CI/CD pipelines for machine learning models.
• Implement and manage infrastructure for model training, deployment, and serving.
• Develop and automate monitoring systems for model performance, drift, and operational health.
• Collaborate with data scientists and engineers to ensure smooth transitions from development to production.
• Containerize applications using Docker and orchestrate them using Kubernetes.
• Implement infrastructure as code (IaC) using tools like Terraform or Ansible.
• Manage cloud-based ML platforms and services (AWS, Azure, GCP).
• Troubleshoot and resolve issues related to ML model deployment and performance in production.
• Contribute to the development of internal tools and frameworks to improve the ML workflow.
• Ensure security, scalability, and reliability of ML systems.

Requirements

• Bachelor's degree in Computer Science, Software Engineering, or a related technical field.
• 3+ years of experience in DevOps, SRE, or MLOps roles.
• Hands‑on experience with MLOps principles and tools (e.g., MLflow, Kubeflow, Airflow).
• Proficiency in scripting languages like Python and shell scripting.
• Experience with containerization technologies (Docker) and orchestration platforms (Kubernetes).
• Strong understanding of cloud platforms (AWS, Azure, GCP) and their associated services.
• Familiarity with CI/CD tools such as Jenkins, GitLab CI, or GitHub Actions.
• Knowledge of monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack).
• Experience with machine learning concepts and workflows is highly advantageous.
• Excellent problem‑solving and debugging skills.

Benefits

Our client offers a competitive salary, comprehensive health and wellness benefits, and opportunities for continuous professional development. You will be part of an innovative team working on cutting‑edge AI technologies, with the flexibility of a Hybrid work arrangement. Experience a dynamic work environment that encourages collaboration and knowledge sharing, located in the beautiful region of Paarl, Western Cape. This role provides a great platform for career growth in the rapidly expanding field of MLOps.