Machine Learning Operations (MLOps) Engineer

About the Role

Our client is seeking a skilled Machine Learning Operations (MLOps) Engineer to enhance their capabilities in AI & Emerging Technologies , based in their Reading office. This role is crucial for bridging the gap between machine learning model development and production deployment, ensuring seamless, reliable, and scalable operations. You will be responsible for building and maintaining the infrastructure and workflows that enable rapid iteration and deployment of ML models. This is a fantastic opportunity for an engineer passionate about automation, CI/CD, and the operationalization of AI, contributing to impactful projects from our Reading hub.

Key Responsibilities

• Design, implement, and manage CI/CD pipelines for machine learning models.
• Develop and maintain infrastructure for training, testing, and deploying ML models in production.
• Monitor the performance and health of deployed ML models, implementing necessary updates and fixes.
• Collaborate with data scientists and software engineers to streamline the ML lifecycle.
• Ensure the scalability, reliability, and security of ML systems and platforms.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in DevOps, Software Engineering, or MLOps.
• Proficiency with cloud platforms (AWS, Azure, or GCP) and containerization technologies (Docker, Kubernetes).
• Experience with CI/CD tools (e.g., Jenkins, GitLab CI, GitHub Actions) and scripting languages (e.g., Python, Bash).
• Solid understanding of machine learning principles and the ML development lifecycle.

Benefits

• Competitive salary and performance-driven incentives.
• Comprehensive health, dental, and vision insurance.
• Access to cutting-edge tools and technologies.
• Hybrid working model offering a balance of office and remote work.
• Opportunities for career growth within a leading tech company in Reading .