Senior Machine Learning Engineer I

About the role

Within the Global Operations organisation, our mission is to build the best customer experience in the fintech industry by delivering an effortless customer experience to all our merchants. We are seeking a skilled and passionate Senior AI / Machine Learning Engineer to join our talented AI team and lead the development of AI models and algorithms that will drive our customer support service to new heights. As a Senior AI / Machine Learning Engineer at SumUp, you will be responsible for building and optimizing state-of-the-art AI models and algorithms. Your expertise with machine learning, deep learning, and LLMs will be crucial in driving the success of our AI-driven initiatives. You will work closely with cross-functional teams, including backend engineers, data scientists and product managers, to translate business requirements into innovative AI solutions. Your contributions will shape the future of our support products and help us stay at the forefront of technological advancements in the field of AI.

Key facts

What you'll do

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.

Design and implement robust monitoring and logging mechanisms to track model performance, data drift, and system health in production.

Conduct experiments and analysis to evaluate model outcomes, identify root causes of issues, and drive iterative improvements.

Partner with product and support teams to define metrics and validate that AI features meet business objectives and user needs.

Contribute to technical documentation and knowledge sharing across the team to ensure maintainability and continuity.

Support the end-to-end lifecycle of machine learning models, from data exploration and prototyping to deployment and ongoing maintenance.

Requirements

Bachelor's degree in Machine Learning, Computer Science or an engineering-related field.

+8 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.

Relevant experience building AI products, such as Chatbot Assistant, RAG system, etc.

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.

You have working proficiency and communication skills in verbal and written English.

Practical notes

The role is based in Berlin, Germany, and operates within a full-time office-first setup. Applicants must be able to work from the Berlin office consistently. The engagement is full-time, and the position requires adherence to standard working hours as defined by company policy. No specific working hours are outlined beyond the expectation of full-time commitment. Travel requirements are not specified beyond the expectation to operate from the Berlin office. No visa sponsorship details are provided in the source material. No application deadline is mentioned in the provided source information.