Machine Learning Engineer

Key Skills

Apache Airflow, ChatGPT, Continuous Integration & Continuous Delivery - CI/CD, DevOps, Docker, ETL frameworks, Git, HuggingFace, Kubernetes-K8s, Large Language Models - LLMs, Machine learning techniques, MLflow, MLOps tools, PySpark, Python Programming, PyTorch, Scikit-learn, Software Development, SQL, TensorFlow, Terraform, Transformer

Job Description

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.

Adyen seeks a Machine Learning Engineer to join our Operations AI team in Madrid. The team focuses on enhancing operations efficiency and improving customer experience through AI automation. We specialize in the technology related to large language models (LLMs) for downstream tasks using Open Source software like HuggingFace or Langchain, and models such as Falcon, Llama or Dolly as well as OpenAI or other proprietary LLMs. 

Key responsibilities:

• Collaborate with the team to build and deploy LLMs for downstream tasks such as ticket routing (text classification), sentiment analysis, and question-answer retrieval, mainly utilizing Open Source technology and libraries.
• 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.
• Containerize applications within Kubernetes clusters and ensure scalable and reliable deployment. Manage and monitor ML models and applications on real time scenarios, ensure their robustness under real live conditions. 
• Employ prompt engineering, embedding calculations and search, vector databases, and other tasks included in the chain of language model applications.
• Stay updated with the latest LLM research and advancements to enhance model efficiency.
• Collaborate with stakeholders to validate hypotheses and design technical solutions, specially when LLMs or other machine learning models are aplicable. 
• Ensure secure and compliant model deployment adhering to data privacy regulations.
• Design and implement APIs or frameworks to facilitate the seamless integration and usage of large language models (LLMs) within various applications and services. Collaborate with software development teams to create user-friendly interfaces that enable efficient interactions with LLMs, promoting their adoption and utilization across the organization.
• Stay up to date with the latest advancements in MLOps tools and practices.

Qualifications:

• 5+ years of professional experience as a Machine Learning Engineer, Data Scientist or MLOps Engineer showing a clear understanding of the end-to-end 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 and SQL. Knowledge of PySpark, Airflow, MLflow, Docker, Kubernetes, and Open Source Python libraries for Data Science and Machine Learning: Pandas, Scikit-learn, Tensorflow/Pytorch, HuggingFace’s Transformers, etc.
• 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, specially for natural language processing. 
• 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:

• Proficiency or previous experience using OpenAI API (GPT-3.5 or GPT-4) or other cloud-based LLMs is highly valued. 
• 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. 

Studies show that women and members of underrepresented communities apply for jobs only if they meet 100% of the qualifications. Does this sound like you? If so, Adyen encourages you to reconsider and apply. We look forward to your application!

What’s next?

Ensuring a smooth and enjoyable candidate experience is critical for us. We aim to get back to you regarding your application within 5 business days. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here. Don’t be afraid to let us know if you need more flexibility.

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.