Machine Learning Operations (MLOps) Engineer

About the Role

Our client is seeking an experienced Machine Learning Operations (MLOps) Engineer to join their forward-thinking team in Oxford . This hybrid role is crucial for bridging the gap between machine learning model development and production deployment, ensuring efficiency, reliability, and scalability. You will design, build, and automate the infrastructure and workflows required to support the end-to-end machine learning lifecycle. This is an exceptional opportunity to work within a renowned academic and technological hub, contributing to the advancement of AI solutions in a collaborative and innovative setting.

Key Responsibilities

• Design, implement, and manage CI/CD pipelines for machine learning models.
• Develop and maintain infrastructure for model training, validation, and deployment.
• Automate and optimize the ML lifecycle, from data ingestion to monitoring and retraining.
• Collaborate with data scientists and engineers to ensure seamless integration of models into production systems.
• Implement monitoring solutions for model performance, drift, and operational health.
• Ensure the scalability, security, and reliability of ML platforms and services.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• 3+ years of experience in DevOps, SRE, or MLOps engineering.
• Strong proficiency in Python and experience with relevant ML libraries and frameworks.
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Familiarity with MLOps tools and best practices (e.g., MLflow, Kubeflow, model registries).
• Understanding of software engineering principles and CI/CD best practices.

Benefits

• Competitive salary and comprehensive benefits package.
• Hybrid work model offering flexibility in Oxford .
• Opportunity to work on cutting-edge AI projects in a leading research environment.
• Support for professional development and continuous learning.
• A collaborative and intellectually stimulating work culture.