.This is AdyenAdyen 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.This is Gen AIOur team's mission is to create a Generative AI platform at Adyen that supports various applications based on LLMs. This involves developing platform-oriented components for deploying an LLM backend within Adyen's GPU cluster in Kubernetes, with features like monitoring, access control, rate limiting, prompt debugging, and experiment tracking. We mainly use Open Source frameworks like HuggingFace and LangChain, and models like Llama or Mixtral. This involves developing platform components and delivering on some of the most promising use cases across different areas within the company.What you'll doBuild and interpret algorithms that power data products at Adyen using Generative AI or NLP techniques.Lead end-to-end development from prompt engineering, few-shot learning, and fine-tuning self-hosted LLMs if needed.Work on Natural Language Processing techniques and LLMs to tackle text classification, sentiment analysis, and summarization of Question-Answering retrieval.Provide technical guidance and mentorship to other data scientists specialized in different domains.Collaborate with cross-functional teams across Adyen to integrate LLM applications in different systems.Ensure efficient data preprocessing and ETL pipelines to create features that feed machine learning algorithms during training.Set up experiments to adjust modeling decisions, perform exploratory analysis, tune hyperparameters, or validate hypothesis selection for the right metric set for each business problem.Report metrics and monitor performance to keep stakeholders updated and ensure a smooth model deployment in production.Iterate with merchants and product audiences, creating algorithms that power state-of-the-art machine learning-based solutions, and explain the reasons behind the executed inference.Who you areYou have 5+ years of professional experience as a Machine Learning or Data Scientist.Proven experience developing, training, validating, benchmarking, and monitoring machine learning algorithms, particularly in the natural language processing domain.Extensive knowledge of machine learning algorithms, including a deep understanding of statistical modeling and Python development tooling and libraries: Pandas, Numpy, Scikit-learn, Pytest, PySpark, SQL, Airflow, and MLflow
