AI/ML Operations Engineer (MLOps)

Placements24; East London; On-site; ZAR 850,000 - 1,250,000; Full time

Benefits offered by this job

Performance bonuses

Health and retirement benefits

Professional development opportunities

Job summary

Placements24 in South Africa seeks an experienced AI/ML Operations Engineer (MLOps) to bridge AI/ML development and production deployment in Queenstown. You will design and maintain scalable infrastructure for training, deploying, monitoring, and managing ML models.

You will collaborate with data scientists and software engineers, build CI/CD for ML pipelines, leverage cloud platforms, and implement IaC and observability to ensure reliable, compliant, and efficient AI systems in a production

Qualifications

• Bachelor's degree in CS, Engineering or related field is required.
• 3+ years in DevOps, SRE, or MLOps roles in production environments.
• Experience with cloud platforms (AWS/Azure/GCP) and containerization (Docker, Kubernetes).
• Proficiency with CI/CD tools (Jenkins, GitLab CI, GitHub Actions) and ML tooling.
• Strong scripting skills (Python, Bash) and infrastructure-as-code practices.

Responsibilities

• Design, implement, and manage CI/CD pipelines for ML models.
• Develop and maintain infrastructure for model training, deployment, and monitoring on cloud platforms.
• Automate operational processes for ML lifecycle management.
• Implement monitoring for model performance, drift, and system health.
• Collaborate with data scientists and software engineers for reliable AI deployment.
• Troubleshoot and resolve production ML issues.

Skills

CI/CD pipelines

Cloud platforms (AWS/Azure/GCP)

Docker

Kubernetes

ML frameworks (TensorFlow, PyTorch)

Scripting (Python, Bash)

IaC (Terraform, CloudFormation)

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

Jenkins

GitLab CI

GitHub Actions

Job description

About the Role

Our client is seeking a skilled and motivated AI/ML Operations Engineer (MLOps) to join their growing team in Queenstown . This role is critical for bridging the gap between AI/ML development and reliable production deployment. You will be responsible for building, automating, and scaling the infrastructure required to train, deploy, monitor, and manage machine learning models efficiently and effectively. This is an excellent opportunity for an experienced DevOps or MLOps professional to establish and refine best practices for AI systems in a production environment.

Key Responsibilities

• Design, implement, and manage CI/CD pipelines for machine learning models.
• Develop and maintain infrastructure for model training, deployment, and monitoring using cloud platforms.
• Automate operational processes related to ML model lifecycle management.
• Implement monitoring solutions to track model performance, drift, and system health.
• Collaborate closely with data scientists and software engineers to ensure smooth deployment and operation of AI systems.
• Troubleshoot and resolve issues in production ML environments.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• 3+ years of experience in DevOps, Site Reliability Engineering, or MLOps.
• Proficiency with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Experience with CI/CD tools (e.g., Jenkins, GitLab CI, GitHub Actions).
• Familiarity with ML frameworks and tools (e.g., TensorFlow, PyTorch, MLflow).
• Strong scripting skills (e.g., Python, Bash) and infrastructure-as-code practices.

Benefits

• Competitive salary and performance-based bonuses.
• Comprehensive health and retirement benefits.
• Opportunities for professional development and acquiring new skills.
• A stable and supportive work environment in Queenstown .
• Exposure to cutting-edge MLOps practices and tools.