Python programmer állások Németországban (rendszertervező)

• Maintain and develop the ocean biogeochemical model code of the HAMOCC model
• Coordinate integration of new process representations developed across multiple projects
• Establish and maintain software quality standards, testing procedures, and documentation

Research and development in the field of distributed computing, communication, and control architectures and their hardware-oriented implementation based on Linux, ROS 2, and etcd – for modular space systems in the smartCASE project and for terrestrial application areas...

• 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

• Build agent loops and orchestration: tool use, structured outputs, business-rule enforcement, graceful failure
• Build the integration layer (via MCP) that lets agents securely call backend systems and business APIs
• Render model output into live, streamed, accessible UI via generative-UI protocols

• developing the control software for the next generations of lithography systems, driving the progress in the semiconductor industry
• implementing best in class embedded control systems on bare metal and on embedded Linux
• contributing to the software architecture definition and design

• Build and maintain backend services and APIs using Java and Python
• Work on event-driven data pipelines based on Kafka
• Take ownership of services end-to-end: design, testing, deployment, monitoring, and iteration
• Ensure code quality, including writing and maintaining automated tests

You design and develop next-generation architecture at the intersection of multi-modal perception, foundation models, behavior learning, and end-to-end autonomous driving....

• Make optimization runs fast enough that customers iterate in minutes, not hours — across problems an order of magnitude larger than today
• Build the data backbone: ingest SAP/ERP exports, Excel reality, and operator knowledge into a clean, versioned, traceable model layer

• Lead the technical lifecycle of ServiceNow and related governance platforms (IRM, Risk, Change, Incident, CMDB, Asset).
• Ensure configurations are secure, scalable, auditable, and aligned with regulatory standards.

You will take a key role in shaping and designing our edge platform for developing, testing, deploying, and operating real-time applications....

• Advise business stakeholders on data-driven opportunities and solutions that support informed decision-making, digitalization, and business growth
• Design end-to-end data solutions for business use cases, from data ingestion and transformation to reusable data products

• 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

• Drive pioneering technical advances to the field of foundation models on structured data, as well as exploring world models for solving business problems.
• Expand the horizon of what is possible by bringing together rich semantic context with large scale business data

Research and development of a multimodal AI assistant that translates natural-language requests into secure actions on real 3D simulation models...

• Identification of the promising state-of-the-art model approaches
• Definition (or refinement) of test cases and driver interaction scenarios
• Benchmarking of available model types under defined boundary conditions (based on requirements from previous investigations)

You develop advanced machine learning-based architectures for automated driving functions and shape the way in which we scale our ML development....

• Build agent loops and orchestration: tool use, structured outputs, business-rule enforcement, graceful failure
• Build the integration layer (via MCP) that lets agents securely call backend systems and business APIs
• Render model output into live, streamed, accessible UI via generative-UI protocols

• Architect and build the high-performance backbone of our data platform
• Focus on distributed computing stability and building effective caching strategies for large-scale operations
• Design ETL pipelines and architect resilient caching for complex dependency resolutions

Drive Architectural Strategy & Scalability: Partner across Data Science, Platform Engineering, and Product teams to design the technical architecture, data pipelines, and orchestration systems required for high-traffic AI services. Ensure the ecosystem supports highly available, low-latency...

Partner with Marketing: Act as a strategic partner to the Marketing organisation and advocate for data-driven decision-making by effectively communicating AI strategy and its alignment with business objectives....