About the company
SumUp is a leading financial technology company, founded in 2012 with the goal of empowering small businesses around the globe. We're the financial partner of choice for more than 4 million merchants in over 35 markets. We collectively build, plan and fine-tune the technology that drives SumUp and empowers small businesses around the world.
Responsibilities
- Architect, design, develop, and deploy our AI solutions and systems in production environments, ensuring reliability, high performance, and scalability.
- Collaborate and communicate closely with data scientists, product managers, developers, and other business stakeholders to bring state-of-the-art AI solutions to Customer Support, enhancing customer experience and improving operational efficiency.
- Develop and maintain ML infrastructure and pipelines to support efficient data processing, model training, and serving.
- Optimize and fine-tune machine learning models to improve accuracy, efficiency, and scalability.
- Collect, preprocess, and clean large text datasets to ensure high-quality input for model training and evaluation.
- Embrace software development principles, best practices, and industry standards, including version control, CI/CD processes, and unit testing frameworks as your day-to-day work.
- Collaborate with cross-functional teams to ensure seamless integration of machine learning solutions into software applications and platforms.
Requirements
- Bachelor's degree in Machine Learning, Computer Science or an engineering-related field.
- +5 years of proven experience working as a Machine Learning Engineer, focusing on building and deploying scalable machine learning or AI solutions and data-driven systems.
- Excellent software development engineering skills to design computationally effective solutions and maintenance in large-scale production environments (data version control, model serving, continuous monitoring & alerting).
- Experience building and deploying ML models using cloud services (AWS, GCP, or Azure).
- Expert in Python and familiarity with MLOps tools (e.g., MLflow, Kubeflow, Airflow, Langfuse).
- Experience with machine learning workflow orchestration and algorithms optimisation, feature engineering pipelines, data ingestion and transformation.
- Good understanding of data pipelines, APIs, containers (Docker), and version control (Git).
- Excellent analytical and problem-solving skills, with strong attention to detail.
- Working proficiency and communication skills in verbal and written English.
Benefits
- Competitive salary and equity participation through our VSOP program.
- 30 days of paid vacation and a 30-day sabbatical after 3 years of employment.
- Contribution to a corporate pension scheme.
- Annual learning and development budget of €2,000.
- Subsidized office lunches, Urban Sports Club membership, and relocation assistance.