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Devops Engineer
hace 2 meses
Job Title: Devops Engineer
About the Role:
We are seeking a highly skilled Devops Engineer to join our Generative AI team in Madrid. As a Devops Engineer, you will play a key role in designing and building the infrastructure to host Large Language Models (LLMs) in-house, ensuring scale, performance, and reliability.
Key Responsibilities:
- Collaborate with the team to design and build the infrastructure to host LLMs in-house, considering scale, performance, and reliability.
- Own the deployment strategy of ML models for downstream tasks such as ticket routing (text classification), 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, from GPUs to vector databases and inference components.
- Develop observability best practices for the whole LLM infrastructure and build the internal framework to monitor LLM behavior, ensuring robustness under real-life conditions.
- 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 (e.g. Git and 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 to prepare and manage data for ML training and inference, as well as model development and deployment frameworks.
- 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.
- Experience in 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 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, including model deployment, monitoring, resources, and infrastructure management, including GPU knowledge.
About Adyen:
Adyen is a financial technology platform that provides payments, data, and financial products to customers like Meta, Uber, H&M, and Microsoft. We are a leader in the payments industry, and our mission is to create a Generative AI platform that enables various applications based on Large Language Models (LLMs).
