Senior ML DevOps Engineer

Job Description
• Architect and implement secure, interoperable solutions using standard frameworks and design patterns, integrating application and infrastructure to achieve scalability and efficiency.
• Develop robust, vendor-agnostic data platforms for AI and machine learning workloads, optimising multi-cloud environments for performance and flexibility.
• Design of structured MLOps pipelines automating and streamlining the models’ lifecycle, from development to serving.
• Design security architectures that protect infrastructure and applications, aligning with risk management strategies and regulatory data protection and security standards.
• Continuously assess and optimise system performance and scalability using advanced metrics and predictive analytics.
• Collaborate with cross-functional teams, including AI developers, business analysts, and IT operations, to ensure architecture aligns with business objectives and technological capabilities.
• Establish CI/CD pipelines to support rapid application development and deployment in dynamic environments, utilising infrastructure-as-code and configuration management tool
• Ensure seamless system integration and cross-platform compatibility through strategic API design, interoperability testing, and continuous benchmarking. Job Requirements
• Expertise in containerisation and orchestration using Docker and Kubernetes for scalable application deployment.
• Expertise in network architecture design, particularly integrating distributed systems with hybrid cloud solutions.
• Comprehensive experience with relational and non-relational databases, optimising them for high-volume transaction processing (e.g., Oracle, PostgreSQL, OpenSearch, MongoDB).
• Proficiency with advanced monitoring tools like Prometheus and Grafana to enhance infrastructure monitoring and real-time alerting.
• Experience with advanced load balancing solutions and caching technologies (e.g. Redis) to support high-traffic applications.
• Knowledge of security and vulnerability scanning tools (e.g., OWASP, SonarQube), implementing secure coding practices including robust encryption and identity management.
• Profound knowledge of version control systems like Git and integration platforms such as Jenkins, GitLab CI.
• Proficiency in distributed streaming and message queue technologies such as Kafka and RabbitMQ to efficiently manage data flows and support scalable data processing architectures.
• Proficiency in using infrastructure-as-code like Terraform or AWS CloudFormation.
• Familiarity with configuration management tools like Ansible for comprehensive system administration.
• Familiarity with AI-powered code assistants (e.g., Amazon Kiro, GitHub Copilot) for accelerating coding processes and enhancing developer productivity.
• Good knowledge of European Commission grant management ecosystem (eGrants) would be an asset.
• Strong problem-solving and analytical skills.
• Strong organisational and time-management skills.
• Strong team spirit and experience working effectively within a collaborative team.
• Capability of integration in an international/multi-cultural environment.
• Excellent communication skills to articulate complex technical concepts.
• Attention to detail in infrastructure design and well-structured documentation.
• Ability to write clean, efficient, and maintainable code