MLOps Engineer

This role focuses on building and maintaining the infrastructure and pipelines required to reliably deploy and monitor machine learning models. The MLOps Engineer will work closely with data scientists and software engineers to ensure that models are scalable, efficient, and meet business requirements.

Key Responsibilities:

Develop and maintain MLOps pipelines for model training, deployment, and monitoring.
Automate model deployment processes and ensure efficient resource utilization.
Implement robust monitoring and alerting systems for model performance.
Collaborate with data scientists to optimize model performance and scalability.
Ensure data quality and integrity throughout the ML lifecycle.
Troubleshoot and resolve issues related to model deployment and performance.

Requirements/Qualifications:

Experience with machine learning model deployment and monitoring.
Proficiency in cloud platforms (e.g., AWS, Azure, GCP).
Experience with containerization technologies (e.g., Docker, Kubernetes).
Strong programming skills in Python.
Familiarity with DevOps principles and practices.
Experience with CI/CD pipelines.
Excellent problem-solving and communication skills.

About the Company:

WITS Innovation Lab is dedicated to advancing technological solutions and fostering innovation within the technology sector. The company focuses on developing cutting-edge applications and services to address evolving industry needs.