Machine Learning Engineer (AI Platform) at N26

Berlin, , Germany -

Full Time

Start Date

Immediate

Expiry Date

24 Dec, 25

Salary

0.0

Posted On

25 Sep, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Machine Learning, Generative AI, Python, AWS, Kubernetes, CI/CD, Observability, Terraform, Kafka, Data Science, Software Engineering, Cross-Functional Collaboration, ML Lifecycle, Monitoring Systems, Distributed Systems, Problem Solving

Industry

Financial Services

Description

About the opportunity At N26, we are building the foundational capabilities that empower product teams and data scientists to integrate AI at scale. As part of the Platform Engineering domain, the AI Platform team is responsible for designing, building, and operating the infrastructure and tooling that make AI use cases scalable, reliable, and easy to adopt, across both Machine Learning and Generative AI domains. We are looking for a Machine Learning Engineer to join our evolving AI Platform team. This role is ideal for someone with strong Python software engineering skills, practical knowledge of ML/GenAI workflows, and the ability to bridge between Data Science and Engineering. You will act as the subject-matter expert of the ML/AI domain within a cross-functional team (with SREs and Backend Engineers), ensuring customer needs are translated into scalable, self-service platform solutions. In this role, you will: Collaborate as part of a cross-functional AI Platform team with Software Engineers, SREs, and internal AI customers (e.g. Data Scientists and Backend Engineers). Design, build, and operate platform components that enable scalable and reliable ML/GenAI workflows (training, deployment, inference, monitoring). Bridge the gap between Data Science theory and technical engineering, ensuring platform abstractions are both customer-friendly and production-ready. Contribute high-quality Python code and apply software engineering best practices (testing, modularity, readability, maintainability). Apply infra/DevOps practices (AWS, Kubernetes, CI/CD, observability) to support production-grade reliability. Work closely with internal customers to understand workflows and requirements, delivering self-service capabilities that allow them to integrate AI features autonomously. Grow your expertise and impact by contributing to design discussions, improving team practices, and gradually taking ownership of platform components. What you need to be successful Background Degree in Computer Science, Data Science, Engineering, or a related technical field. Solid grasp of ML/GenAI lifecycle needs, software engineering principles, and modern platform infrastructure. Profile 2 - 4 years of experience delivering production-grade ML systems or ML platform components. Strong Python development skills, with experience building robust, maintainable codebases. Familiarity with cloud-native ML infrastructure, particularly AWS (e.g., SageMaker, Lambda, ECS, Bedrock). Understanding of the ML lifecycle and experience contributing to capabilities like pipelines, model registries, feature stores, or monitoring systems. Exposure to Terraform, Kubernetes, Kafka, or similar distributed systems. Ability to collaborate cross-functionally and contribute to technical discussions with diverse stakeholders. Nice to haves Experience with Generative AI workflows (RAG pipelines, LLM APIs, prompt orchestration). Experience working in platform or enablement teams. Familiarity with TypeScript (for frontends or SDKs). Contributions to open source ML/infra tooling. Traits Motivated by platform enablement, building systems that help others succeed. Collaborative team player with clear, structured communication. Curious and eager to learn, with a growth mindset. Pragmatic problem solver who balances engineering quality with delivery. What’s in it for you: Accelerate your career growth by joining one of Europe’s most talked about disruptors. Employee benefits that range from a competitive personal development budget, work from home budget, discounts to fitness & wellness memberships, language apps and public transportation. Come together with your team in the office for a dedicated day of teamwork each week, plus another day of your choice, and enjoy the flexibility of remote work the rest of the time. Some roles may require additional in-office presence. As an N26 employee you will have access to a Premium subscription on your personal N26 bank account. As well as subscriptions for friends and family members. Additional day of annual leave for each year of service. A high degree of autonomy and access to cutting edge technologies - all while working with a friendly team of peers of diverse nationalities, life experiences and backgrounds. A relocation package with visa support for those who need it. Who we are N26 has reimagined banking for today’s digital world. Technology and design empower everything we do and it’s how we are building the global banking platform the world loves to use. We've eliminated physical branches, paperwork, and hidden fees for an elegant digital experience and supreme savings. Giving people the power to live and bank their way is what gets us out of bed in the morning and inspires the work that we do. We are headquartered in Berlin with offices in multiple cities across Europe, including Vienna and Barcelona, and a 1,500-strong team of more than 80 nationalities. Sounds good? Apply now for this position. Equal Opportunities: We recognize that our strength lies in our people and the varied perspectives they bring to our workforce. We strive to build talented and diverse teams to drive our business success and empower our people to reach their full potential. We genuinely welcome and encourage applications from people of all backgrounds, cultures, genders, sexual orientations, abilities, neurodiversities, and ages. We're committed to creating an inclusive workspace where everyone feels valued and respected, free from harassment and discrimination. If there's anything you need to make the application process work for you, please let us know by reaching out to candidate.exp@n26.com. Visit our website to learn more about Diversity, Equity, & Inclusion at N26.

Responsibilities

The Machine Learning Engineer will collaborate with a cross-functional AI Platform team to design, build, and operate platform components for scalable ML/GenAI workflows. They will bridge the gap between Data Science and Engineering, ensuring customer needs are met with self-service platform solutions.