Machine Learning Operations (MLOps) Engineer

About the Role

Our client is seeking a skilled Machine Learning Operations (MLOps) Engineer to join their growing team in Oxford . This role is crucial for bridging the gap between machine learning model development and production deployment, ensuring that AI systems are reliable, scalable, and maintainable. You will be responsible for building and managing the infrastructure, tools, and processes required to streamline the end-to-end ML lifecycle, from experimentation and training to deployment and monitoring. If you have a passion for automation, infrastructure, and ensuring the smooth operation of complex AI systems, this is an excellent opportunity to make a significant impact.

Key Responsibilities

• Design, build, and maintain robust CI/CD pipelines for machine learning models.
• Implement and manage infrastructure for training, deploying, and monitoring ML models in production.
• Develop and enforce best practices for version control, testing, and reproducibility in ML workflows.
• Collaborate with data scientists and software engineers to operationalize ML models efficiently.
• Monitor model performance in production, troubleshoot issues, and implement necessary updates or fixes.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Experience (3+ years) in software engineering, DevOps, or a dedicated MLOps role.
• Proficiency in scripting languages (e.g., Python) and experience with cloud platforms (AWS, Azure, GCP).
• Familiarity with containerization technologies (Docker, Kubernetes) and CI/CD tools (e.g., Jenkins, GitLab CI).
• Understanding of the machine learning lifecycle and common ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).

Benefits

• Competitive salary and performance-based bonuses.
• Comprehensive health, dental, and vision insurance.
• Opportunities for professional development and training in cutting-edge technologies.
• Engaging work environment with a focus on innovation and collaboration.
• Modern office facilities and a supportive team culture in Oxford .