Junior python állások, munkák rendszertervező kategóriában

• Kapcsolattartás az ügyfelekkel, igények felmérése és tanácsadás
• Azure Function App fejlesztés
• Dokumentálás
• Programozás Pythonban
• Azure infrastruktúra tervezés és karbantartás
• Rendszeres ellenőrzés, frissítés és teljesítmény optimalizálás Azure környezetben
• Fejlesztések tervezésében aktív részvétel

• building the data infrastructure
• designing and implementing the neural-process architecture
• you will develop scalable data pipelines for heterogeneous environmental datasets
• you will design and implement neural-process-based architectures for spatio-temporal prediction

• Design, development, and operation of data-driven PMO reporting and process solutions using Microsoft Power Platform, Python, and cloud technologies
• Integration and harmonization of data from different systems related to planning, reporting, and project management

• 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

• Administration and support of Cloudera Private Cloud Platform (PCP) and Cloudera Data Platform (CDP) environments
• Deployment, configuration, maintenance, and troubleshooting of Cloudera clusters and services
• Management of containerized environments using Docker/Podman and Kubernetes/OpenShift

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...

• Building, configuring and maintaining bare metal hosts and Kubernetes clusters to run GPU/AI workloads
• Designing and operating NVIDIA AI related software stack (Slurm, Run AI)
• Providing customized application support for AI related workloads

Build enterprise cloud infrastructure that provides European data sovereignty and hyperscaler-grade capabilities. You'll work on SAP Cloud Infrastructure, solving complex distributed systems challenges at scale: multi-region networking, container orchestration, storage systems, and the APIs that...

The mathematics behind the models. A model means exactly one thing, and it still means that after it reaches a solver. The algebra underneath is yours, and so is the call on what the engine should be able to express next and what it should refuse....

• 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

• 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

• Design secure reference architectures and patterns for AI platforms and AI applications
• Consult product, data science, and platform teams on secure AI design and implementation
• Secure AI systems against data poisoning, model theft, adversarial attacks, and other AI‑specific threats

• 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

• 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

• 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