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AI Infrastructure Engineer
- oxford, oxfordshire, OX1 1AA, United Kingdom
- Permanent·Hybrid
- Full time
- £70,000 - £70,000 Per Annum
Job Description
About the Role
Our client is seeking a skilled AI Infrastructure Engineer to join their team in Oxford . This role is critical for building and maintaining the robust, scalable, and efficient infrastructure required to support our advanced AI and machine learning operations. You will be responsible for managing cloud resources, optimizing compute and storage, and ensuring the reliability of our AI development and deployment environments. The ideal candidate has a strong background in systems engineering, cloud computing, and a passion for enabling AI innovation through solid infrastructure.
Key Responsibilities
- Design, implement, and manage scalable cloud infrastructure for AI/ML workloads (e.g., AWS, Azure, GCP).
- Optimize compute, storage, and networking resources for AI training and inference performance.
- Develop and maintain CI/CD pipelines for machine learning models and infrastructure automation.
- Implement monitoring, logging, and alerting systems to ensure the availability and performance of AI services.
- Collaborate with data scientists and ML engineers to understand their infrastructure needs and provide solutions.
- Ensure the security, reliability, and cost-effectiveness of the AI infrastructure.
Requirements
- Bachelor's degree in Computer Science, Engineering, or a related technical field.
- Proven experience as an Infrastructure Engineer or DevOps Engineer with a focus on AI/ML environments.
- Strong expertise in cloud platforms (AWS, Azure, or GCP) and containerization technologies (Docker, Kubernetes).
- Experience with infrastructure-as-code tools (e.g., Terraform, Ansible).
- Familiarity with machine learning workflows and MLOps principles.
- Excellent scripting skills (e.g., Python, Bash) and problem-solving abilities.
Benefits
- Competitive salary and comprehensive benefits package.
- Hybrid working model offering flexibility between office and remote work.
- Opportunities to work with cutting-edge AI technologies and infrastructure.
- Support for continuous learning and professional development.
- A collaborative team environment focused on technological advancement.