Senior Machine Learning Engineer II

Das ist der Job

Experience using GenAI / LLM API and evaluating LLM models in production.

Darum lohnt es sich

What You’ll Be Doing You will be the dedicated technical leader for the Operations AI team, focused on designing, developing, and deploying high-performance, scalable ML/AI solutions in production environments. A true team player attitude who thrives on cross‑functional collaboration.

Why You Should Join the Company Opportunity to work with the team globally on large‑scale fintech products used by millions of businesses worldwide, from our Berlin office. Numerous other benefits such as Urban Sports Club subsidy, Kita placement assistance, subsidised office lunches.

Referral Bonus: earn additional rewards by referring talented individuals to join the team. The Senior AI/ML Engineer role is critical for developing and deploying the next generation of AI-driven solutions that automate support and drastically improve the experience for both our merchants and support agents.

You will be a key expert who builds and maintains the ML infrastructure and tooling that powers our core products using advanced AI/ML models. Architect, design, develop, and deploy our AI solutions and systems into production environments, ensuring reliability, high performance, and scalability.

Take ownership and technical leadership in the development and maintenance of main AI products, including the AI Assistant (automating ~40% of merchant requests), AI Translation (enabling cross-language agent service), and the AI Agent Copilot.

Develop and maintain ML infrastructure and pipelines to support efficient data processing, model training, serving, and continuous monitoring. Optimise and fine‑tune machine learning models, and 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 (Git), CI/CD processes (GitHub actions), and unit testing frameworks.

Collaborate closely with Data Scientists, Product Managers, Developers, and other business stakeholders to enhance customer experience and improve operational efficiency globally. Complex Onboarding: Rapidly master a large, existing AI assistant infrastructure, starting immediately with working on behavior improvements and agentic rollouts.

Pilot and Innovation: Lead the creation of the pilot for the Voice Assistant and design how to leverage current AI assistant components to empower new channels.

You’ll Be Great for This Position If You Have 7+ years of proven experience as a Machine Learning Engineer or AI Engineer, focusing on building and deploying scalable machine learning or AI solutions and data‑driven systems.

Expert-level Python proficiency and excellent software development engineering skills for designing computationally effective solutions in large‑scale production. Strong prior experience as an ML or AI engineer, with models in production, and a strong understanding of artificial intelligence, machine learning, and deep learning concepts.

Experience building and deploying ML models using Cloud platforms (AWS, GCP, or Azure). Familiarity with MLOps tools (e.g., MLFlow, Kubeflow, Airflow, Langfuse) and hands‑on experience with Kubernetes, Git, and Airflow. Good understanding of data pipelines, API design, containers (Docker), and version control (Git).

Experience building, maintaining, and scaling APIs, and deployment using CI/CD pipelines in GitHub actions. Self‑drive, proactiveness, and high adaptability in a fast‑paced environment, with a commitment to data governance, quality, and ownership.

A passion for AI technology, excited to power the company’s next‑generation automated support tools, and able to translate complex concepts to non‑technical stakeholders. This involves an office‑first setup.

Commitment to Diversity and Inclusion: a workplace that values and promotes diversity, fostering an inclusive environment where everyone’s perspectives are respected and embraced. Enrollment into our Virtual Stock Option programme: you will own a stake in the company’s future success.

A dedicated annual learning and development budget of €2000 for attending conferences and/or advancing your career through further education. A corporate pension scheme where we match up to 20% of your contributions. Generous time off: enjoy 28 days of paid leave plus public holidays and special leave days.

Break4me: a 1‑month sabbatical after 3 years of service. Equal Employment Opportunity Statement The company is proud to be an Equal Employment Opportunity employer, committed to building a safe, respectful, and diverse workplace where everyone can thrive. #J-18808-Ljbffr