Lead AI Engineer - Machine Learning Operations

Placements24; Cape Town; Hybrid; ZAR 1,800,000 - 2,400,000; Full time

Benefits offered by this job

Performance bonuses

Healthcare coverage

Stock options

Development budget

Forward-thinking culture

Job summary

Placements24 in Cape Town seeks a Lead AI Engineer specializing in MLOps to build and scale production AI systems. You will lead a team of engineers, architect robust pipelines, and ensure reliable deployment, monitoring, and performance across cloud environments.

The role requires deep expertise in ML operations, CI/CD for ML, and strong leadership. A dynamic, high-impact position offering growth and substantial incentives in a fast-paced tech hub in Cape Town.

Qualifications

• Bachelor's or Master's degree in CS/Engineering or related field.
• 7+ years of software engineering, with 3+ years in MLOps or AI infrastructure.
• Proven CI/CD pipelines for ML models.
• Strong cloud platform experience and containerization (Docker/Kubernetes).
• Experience with Kubeflow/MLflow/Airflow.
• Excellent leadership, communication, and problem-solving skills.

Responsibilities

• Design and maintain scalable MLOps pipelines for training, deployment, and monitoring.
• Lead and mentor MLOps and AI engineers, fostering best practices.
• Develop strategies for model versioning, performance tracking, and A/B testing in production.
• Collaborate with data scientists and software engineers across the ML lifecycle.
• Ensure security, compliance, and performance of AI systems in cloud environments.
• Troubleshoot deployment, performance, and infrastructure issues in production.

Skills

MLOps leadership

CI/CD for ML

Cloud platforms

Team mentoring

ML fundamentals

Education

Bachelor's or Master's in CS/Engineering

Tools

Kubeflow

MLflow

Airflow

Docker

Kubernetes

Job description

About the Role

Our client is seeking an experienced and visionary Lead AI Engineer specializing in Machine Learning Operations (MLOps) to join their cutting-edge technology hub in Cape Town . This role is critical for establishing and scaling the infrastructure and processes required to deploy, monitor, and maintain AI models in production environments. You will lead a team of talented engineers, architecting robust MLOps pipelines that ensure the reliability, scalability, and efficiency of our AI solutions. This is an unparalleled opportunity to shape the operational landscape of AI within a fast-paced, innovative company, fostering a culture of operational excellence and continuous improvement.

Key Responsibilities

• Design, build, and maintain scalable and resilient MLOps pipelines for automated model training, deployment, and monitoring.
• Lead and mentor a team of MLOps and AI engineers, fostering best practices and technical excellence.
• Develop and implement strategies for model versioning, performance tracking, and A/B testing in production.
• Collaborate with data scientists and software engineers to streamline the end-to-end machine learning lifecycle.
• Ensure the security, compliance, and performance of AI systems deployed in cloud environments (e.g., AWS, Azure, GCP).
• Troubleshoot and resolve complex issues related to model deployment, performance degradation, and infrastructure failures in Cape Town .

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Minimum of 7 years of experience in software engineering, with at least 3 years focused on MLOps or AI infrastructure.
• Proven expertise in building and managing CI/CD pipelines for machine learning models.
• Strong proficiency in cloud platforms (AWS, Azure, or GCP) and containerization technologies (Docker, Kubernetes).
• Experience with ML orchestration tools such as Kubeflow, MLflow, or Airflow.
• Excellent leadership, communication, and problem-solving skills, with a deep understanding of AI/ML principles.

Benefits

• Highly attractive salary with significant performance bonuses.
• Extensive healthcare coverage and wellness programs.
• Generous stock options and long-term incentives.
• Professional development budget for conferences, certifications, and training.
• A dynamic, inclusive, and forward-thinking work culture in Cape Town .