Machine Learning Operations (MLOps) Engineer

About the Role

Our client is seeking a skilled Machine Learning Operations (MLOps) Engineer to join their cutting-edge technology team in Reading . This role is critical for bridging the gap between machine learning model development and reliable production deployment. You will be responsible for building and maintaining scalable, automated ML pipelines, ensuring the efficiency, reliability, and performance of AI systems in production. This is an exciting opportunity to work with advanced technologies, streamline ML workflows, and contribute to the successful delivery of AI-powered products within a dynamic and collaborative environment.

Key Responsibilities

• Design, build, and maintain robust CI/CD pipelines for machine learning models.
• Automate the deployment, monitoring, and management of ML models in production environments.
• Implement infrastructure for data versioning, model versioning, and experiment tracking.
• Collaborate closely with data scientists and software engineers to ensure smooth integration and operation of ML systems.
• Troubleshoot and resolve issues related to ML model performance, scalability, and reliability.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Proven experience in MLOps, DevOps, or Software Engineering with a focus on ML systems.
• Strong proficiency in scripting languages (e.g., Python) and containerization technologies (e.g., Docker, Kubernetes).
• Experience with cloud platforms (AWS, Azure, or GCP) and their ML services.
• Understanding of machine learning concepts and lifecycles is essential for success in this role.

Benefits

• Competitive salary and performance-based bonus.
• Comprehensive health, dental, and vision insurance.
• Pension scheme and life assurance.
• Opportunities for professional development and certifications.
• A collaborative hybrid working environment in Reading .