Data engineer állások, munkák Németországban

How will robots collaborate with humans in the future? We develop intelligent systems that understand language, perceive their environment, interpret situations, and act autonomously in the physical world. In our team, we combine Foundation Models, Agentic AI, Computer Vision, and Robotics to...

• Lead develop AI services from PoC to Production
• Lead the development of a best practice framework for AI development (both narrow and GenAI) for all dev streams and teams
• Lead the definition, evolution and drive the setup of infrastructure architecture for the AI applications we are building

Lead the lifecycle of ICT risk assessments, from initial risk identification and execution to final remediation monitoring....

• Measuring and evaluating digital employer branding campaigns across paid, owned, and organic channels, using web analytics to assess channel contribution
• Applying tracking frameworks including UTM parameters, conversion tracking, and attribution models to assess campaign ROI and media efficiency

Architect AI Workflows: Design, deploy, and govern E2E, multi-step Agentic AI solutions and automations that target high-volume processes, cross-team friction, and manual back-office tasks....

• Single point of contact for the research faculty and group leaders on specialist IT, data and computing needs
• Assessment of research IT needs and their translation into actionable demands
• Onboarding and key user management: making sure that our researchers can work productively from day one

• Keep the operational backbone running – ticketing, HubSpot, and our data room (Dock), clean and up to date.
• Take customer questions and route them internally – the "travel agent" who gets every request to the right people fast.

• The customer from the first calls on: take apart their decision problem live, pre-sales, and turn it into a first mini model.
• Scope and lead the development project end-to-end; own the result, not just the planning and organisation.

• Tech Stack: Python (Django/FastAPI), PostgreSQL/TimescaleDB, Redis, Celery, Docker, AWS, GitLab CI/CD, Sentry, Grafana
• Your Focus: API design & architecture, backend integrations, data flows, system reliability and scalability

sound coding skills, particularly in Python, with proven experience in the development, implementation and further development of AI-based solutions and the responsible assumption of technical and specialist development tasks...

Up for a new challenge? In our Transaction Services team you experience how global banking works from the inside. As part of product management, you'll learn to balance client needs, regulatory requirements, operational scalability, and commercial performance to create products that keep...

Support end-to-end governance of third-party relationships — onboarding, oversight, contract governance, performance monitoring, and exit planning — ensuring compliance with internal policies and regulatory requirements....

Up for a new challenge? Join our Transaction Service team, where we combine operational excellence with strategic relevance and put your finger right on the pulse of international business as we help our clients run their operations efficiently, securely, and globally....

Where you belong: Where you belong: ...

Design, train, and evaluate machine learning models for manufacturing use cases such as quality prediction, anomaly detection, predictive maintenance, and process optimisation, covering the full ML lifecycle from problem definition to performance tuning....

In close collaboration with Process Owners you analyze existing processes, identify AI‑ and agent‑based use cases, and design and build AI‑driven process architectures by integrating available AI platforms, technologies, agents, data, and knowledge sources....

Perform research in the field of closed-loop medication systems, aiming at point-of-care antibiotics level measurement from whole blood and utilizing this data for automated dose control...

• Define, maintain, and evolve DLP governance requirements, internal security policies, and written rules in alignment with the ICT risk framework and regulatory expectations.
• Establish clear requirements for information handling, classification, data transfer, endpoint usage, and media protection etc.

• Contribute biological expertise and domain knowledge to the development, validation, and implementation of AI-supported candidate gene discovery approaches.
• Identify, analyse, integrate, and interpret complex multi-omics datasets to support candidate gene discovery and trait development.

• Own the full commercial performance of your categories, including P&L, inventory health, growth, and profitability drivers
• Define and execute category strategies based on customer behavior, market trends, competitor dynamics, and commercial opportunities