This is Adyen

Adyen provides payments, data, and financial products in a single solution for top-tier customers like Meta, Uber, H&M, and Microsoft. As the leading financial technology platform, everything we do at Adyen is engineered for ambition and innovation.

Position: DevOps Engineer - Generative AI Team

Adyen is seeking a skilled MLOps or DevOps Engineer to join our Generative AI team in Madrid. This team's mission is to create a cutting-edge Generative AI platform, leveraging Large Language Models (LLMs) to power various applications. The focus is on developing platform components for internal deployment and delivering comprehensive solutions that drive operational efficiency. Use cases such as support case routing and sentiment analysis highlight the adaptability of AI, revolutionizing workflows across our organization.

Key Responsibilities

• Collaborate with the team to design and build infrastructure for hosting LLMs in-house, ensuring scalability, performance, and reliability.
• Own the deployment strategy of ML models for tasks like ticket routing, summarization, sentiment analysis, and question-answer retrieval.
• Automate the ML pipeline using MLOps tools and practices, optimizing for scalability and performance.
• Containerize applications and manage Kubernetes deployments along with the necessary infrastructure from GPUs to vector databases and inference components.
• Develop best practices for observability within the LLM infrastructure, building frameworks for monitoring LLM behavior under real-life conditions.
• Design and implement APIs, services, or frameworks to facilitate seamless integration and usage of LLMs across various applications and services.
• Stay updated with the latest advancements in MLOps tools and practices.

Qualifications

• 5+ years of professional experience as a DevOps Engineer, MLOps Engineer, ML Engineer, or Data Engineer.
• Strong software development skills, including version control (e.g., Git, preferably on GitLab), coding best practices, debugging, unit and integration testing.
• Proficient in Python, Airflow, MLflow, Docker, Kubernetes, and ArgoCD.
• Proficiency with observability tools such as Prometheus, Logsearch, Kibana, and Grafana.
• Knowledge of data pipelines and ETL processes for ML training and inference, as well as model development and deployment frameworks.
• Solid understanding of DevOps best practices, CI/CD concepts, and experience in implementing these practices.
• Ability to diagnose and resolve model performance, scalability, and deployment issues.
• Familiarity with monitoring tools for tracking model performance, resource utilization, and system health, including logging and error monitoring for ML models and applications.

Desirable Additional Requirements

• Knowledge of ETL pipelines using PySpark and Airflow for data preprocessing and model training.
• Clear understanding of the end-to-end machine learning lifecycle.
• Experience with Helm for packaging and deploying applications on Kubernetes and with Kustomize for managing Kubernetes configurations.
• Familiarity with infrastructure as code tools like Terraform.
• Experience with Open-source Machine Learning frameworks like Huggingface Transformers.
• General LLMOps experience, including model deployment, monitoring, resource and infrastructure management, including GPU knowledge.

Our Diversity, Equity, and Inclusion Commitments

At Adyen, we believe that diverse perspectives drive innovation and momentum. Our unique approach is the product of our varied backgrounds and cultures. We invite you to bring your unique voice to our team and help us tackle our unique business and technical challenges. Be your true self at Adyen, regardless of who you are or where you come from.

Studies show that women and members of underrepresented communities often apply for jobs only if they meet 100% of the qualifications. If this sounds like you, we encourage you to reconsider and apply. We look forward to your application!

What’s Next?

Ensuring a seamless and enjoyable candidate experience is a priority for us. You can expect to hear back about your application within 5 business days. While our interview process typically takes about 4 weeks, this may vary depending on the role. Learn more about our hiring process . Feel free to let us know if you need more flexibility.