DevOps Engineer

hace 4 días

Madrid, Madrid, España Adyen A tiempo completo
Adyen's Generative AI Platform Engineer

Adyen is seeking a skilled DevOps Engineer to join our Generative AI team in Madrid. As a key member of this team, you will play a crucial role in developing and deploying a platform that enables various applications with Large Language Models (LLMs).

Key Responsibilities:

  • Design and build the infrastructure to host LLMs in-house, ensuring scale, performance, and reliability.
  • Own the deployment strategy of ML models for downstream tasks such as ticket routing, summarization, sentiment analysis, and question-answer retrieval.
  • Automate the ML pipeline using MLOps tools and practices, optimizing it for scalability and performance.
  • Containerize applications and manage Kubernetes deployments, as well as the infrastructure needed to deploy LLMs internally.
  • Develop observability best practices for the whole LLM infrastructure and build the internal framework to monitor LLM behavior.
  • Design and implement APIs, services, or frameworks to facilitate the seamless integration and usage of LLMs within various applications and services.
  • Stay up-to-date 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, 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.
  • Solid understanding of DevOps best practices and tools to automate software development and deployment processes, and CI/CD concepts and experience in implementing these practices.
  • Ability to diagnose and resolve model performance, scalability, and deployment issues.
  • Familiarity with monitoring tools to track model performance, resource utilization, and system health.

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 customizing and managing Kubernetes configurations.
  • Familiarity with infrastructure as code with tools like Terraform.
  • Experienced with Open-source Machine Learning frameworks like Huggingface Transformers.
  • General LLMOps experience is a plus, including model deployment, monitoring, resources, and infrastructure management, including GPU knowledge.

About Adyen:

Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition.

Language: en-US

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