Machine Learning Infrastructure Engineer - Madrid, España - Adyen

Adyen

Empresa verificada

Madrid, España

hace 6 días

Publicado por:

Isabel García

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Descripción

This is 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.

For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers.

We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster.

Key responsibilities:

Collaborate with the team to deploy LLMs for downstream tasks such as ticket routing (text classification), summarization, sentiment analysis, and questionanswer retrieval.
Develop and manage ETL pipelines using PySpark and Airflow for data preprocessing and model training. Organize the orchestration of pipelines for ETL and machine learning training to streamline model development.
Automate the ML pipeline using MLOps tools and practices and optimize it for scalability and performance.
Develop observability best practices for the whole LLM infrastructure and build the internal framework which allows the team to monitor the LLM behavior to ensure their robustness under real life conditions.
Stay up to date with the latest advancements in MLOps tools and practices.

Qualifications:

5+ years of professional experience as a Machine Learning Engineer, DevOps or MLOps Engineer showing a clear understanding of the endtoend machine learning lifecycle
Strong software development skills, including: version control (e.g. Git and preferable on Gitlab), coding best practices, debugging, unit and integration testing.
Proficient in Python. Knowledge of PySpark, Airflow, MLflow, Terraform, Docker, Kubernetes, Helm, Kustomize 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.

Desirable additional requirements:

Experienced with Opensource Machine Learning frameworks like Huggingface Transformers.
General LLMOps experience is a plus, including model deployment, monitoring, resources, and infrastructure management.

Our Diversity, Equity and Inclusion commitments
Our unique approach is a product of our diverse perspectives. This diversity of backgrounds and cultures is essential in helping us maintain our momentum.

Our business and technical challenges are unique, and we need as many different voices as possible to join us in solving them - voices like yours.

No matter who you are or where you're from, we welcome you to be your true self at Adyen.

What's next?
This role is based out of our Madrid office. We are an office-first company and value in-person collaboration; we do not offer remote-only roles.