Senior Machine Learning Engineer (f/d/m)

Headquarter

Trade Republic

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Please note that this position is based in Berlin, Germany - relocation support is provided if required. 

LIGHTHOUSE FOR TALENT 

 

At Trade Republic, we are on a mission to empower everyone to create wealth with easy, safe and free access to the financial system. With over four million customers we are the largest savings platforms in Europe, with users holding over €35 billion on our platform.

 

We are seen as the go-to-destination for top talent from across the globe. Everyday we strive to make Trade Republic a great environment to do the best work of your life, surrounded by exceptional, caring and passionate colleagues. In addition to learning and growing with a world-class team, you will build a destination for millions of people across Europe to create wealth.



ABOUT THE TEAM

 

The Data Platform department mission at Trade Republic is to build a scalable, secure, and cost-efficient data platform by providing self-service products that empower Trade Republic teams to innovate, make data-driven decisions, and achieve full data ownership. By fostering a world-class team of professionals, we ensure continuous improvement and operational excellence, setting new standards in data-driven finance. For example, we offer the tools that each data producer can use to ingest their data into our data lake, develop data pipelines, schedule and orchestrate workloads, build dashboards, and discover data.

 

Our Machine Learning Platform team is dedicated to making Trade Republic the safest, most efficient, and effective platform for building wealth. AI is a core part of this vision, and our mission is to provide state of the art tools and infrastructure that enable teams to move quickly from experimentation to production and innovate faster.

 

We develop products primarily with Python and SQL, leveraging AWS services extensively. We manage infrastructure using Terraform, keeping everything as code, and rely on GitHub actions for providing a secure and efficient development environment. Kafka serves as our core messaging layer, we use Spark and Flink for critical applications. We build and maintain our observability systems on LGTM stack.



WHAT YOU WILL BE DOING

In collaboration with engineers and data scientists , you will:

  • Build our Machine Learning Platform with tools and infrastructure for advanced data analysis, experimentation, training, evaluation, validation, and deployment of machine learning models and data-driven products
  • Design and build tools to detect model degradation, data drift; ensure the reliability of models in business-critical applications.
  • Build CI/CD pipelines and improve automation and continuous deployment and integration of machine learning models
  • Deliver technical solutions from design through implementation and operation.
  • Drive continuous improvement in MLOps engineering best practices, ensuring adherence to company-wide standards, including security.
  • Identify and resolve technical challenges, addressing risks proactively.
  • Mentor team members through code and architecture reviews, promoting growth and upskilling opportunities.

 

WHAT WE'RE LOOKING FOR

  • Extensive experience in MLOps. Bonus points if you have a MSc or PhD in Computer Science, Engineering or a related field.
  • Expertise in designing, implementing and operating machine learning  pipelines; tooling and infrastructure for large-scale machine learning applications, going from simple expert-driven rules to GNNs.
  • Knowledge of tooling and infrastructure for multiple types of algorithms such as random forest, boost family and graph-based models.
  • Hands-on experience in Terraform, Kubernetes and building CI/CD pipelines.
  • A research-driven mindset that balances rapid delivery with continuous improvement of techniques and tools.
  • Proven ability to influence and guide technical teams.
  • Skilled in balancing fast feature delivery with scalable, long-term solutions.
  • Comfortable navigating uncertainty while shaping vision and strategy.
  • Bonus points for experience with GPU computing, PyTorch ecosystem and distributed systems like Spark or Flink



WHY YOU SHOULD APPLY NOW 

 

At Trade Republic you will get to do the best work of your career. We are a destination for people who are exceptional at what they do. Every day, we strive to build a world-class team and provide the space for people to do their best. We have a relentless ambition of raising the bar and expect the best from ourselves. Through our dedicated people-first management approach and transparent career paths, you will have the opportunity to develop and grow your career like never before. And because you are surrounded by a diverse team of high performers, you will be learning every day.

You will play an important role in fixing one of the largest challenges we face - closing the pension gap and democratizing wealth. Trade Republic is a place where your job, your career and your passions intersect. If this gets you fired up, just like it does for all of us at Trade Republic, then reach out!

Trade Republic embraces diversity and strives for equal opportunity for everyone. We are committed to building a team that represents a variety of backgrounds, characteristics, perspectives and skills. We encourage applicants of diverse gender, age, sexuality, religion, ethnicity, disability status and parental status to apply to our roles, or those from other intersecting minority groups not listed. The more diverse and inclusive we are as a team, the greater our work will be. If we can support you on DEI related questions during the interview process, please reach out to talentacquisition@traderepublic.com.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Architecture AWS CI/CD Computer Science Data analysis Data pipelines Distributed Systems Engineering Finance Flink GitHub GPU Kafka Kubernetes Machine Learning ML models MLOps PhD Pipelines Python PyTorch Research Security Spark SQL Terraform

Perks/benefits: Career development Relocation support Startup environment

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