AI​/ML Operations; MLOps) Engineer

Our client, a frontrunner in AI and Emerging Technologies, is seeking a proactive and skilled AI/ML Operations (MLOps) Engineer to join their team in Mossel Bay, Western Cape . This critical role focuses on bridging the gap between machine learning model development and reliable production deployment. You will be responsible for building, automating, and maintaining the infrastructure and processes that enable the efficient and scalable deployment, monitoring, and management of machine learning models.

The ideal candidate has a strong background in software engineering, Dev Ops, and machine learning fundamentals, with practical experience in MLOps tools and practices. You will work closely with data scientists and ML engineers to streamline the ML lifecycle, ensuring models deliver continuous value in production. This position offers a unique opportunity to shape the operational excellence of AI systems within a forward-thinking organization.

• Design, implement, and manage CI/CD pipelines for machine learning models.
• Automate the deployment, scaling, and monitoring of ML models in production environments.
• Develop and maintain infrastructure for training, testing, and serving ML models.
• Implement tools and strategies for model versioning, lineage tracking, and reproducibility.
• Monitor model performance in production and establish alerting mechanisms for issues.
• Collaborate with data scientists and ML engineers to optimize model deployment workflows.
• Ensure the reliability, scalability, and security of the ML infrastructure.
• Manage containerization and orchestration platforms (e.g., Docker, Kubernetes) for ML workloads.
• Contribute to the selection and integration of MLOps tools and technologies.
• Troubleshoot and resolve operational issues related to ML systems.

• Bachelor's degree in Computer Science, Software Engineering, or a related technical field.
• Minimum of 4 years of experience in software development, Dev Ops, or MLOps.
• Proven experience implementing MLOps best practices and tools (e.g., MLflow, Kubeflow, Seldon Core).
• Strong understanding of machine learning concepts and workflows.
• Proficiency in programming languages such as Python.
• Experience with cloud platforms (AWS, Azure, or GCP) and their container services (e.g., EKS, AKS, GKE).
• Expertise in CI/CD tools (e.g., Jenkins, Git Lab CI, Git Hub Actions).
• Familiarity with infrastructure as code (IaC) tools like Terraform or Cloud Formation.
• Knowledge of monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack).
• Excellent scripting and automation skills.
• Strong problem-solving and communication abilities.

• Competitive salary and performance incentives.
• Comprehensive medical, dental, and vision coverage.
• Generous paid time off and holidays.
• Opportunities for professional growth and skill development.
• Exposure to cutting-edge AI technologies and practices.
• Supportive and collaborative team environment.
• Retirement fund contributions.
• Annual company retreats.