Python programmer állás, munka

• Development and testing of Windows software based on Qt.
• Creating requirements and test cases in Polarion
• Working responsibly within development teams to solve complex tasks in a regulatory environment
• Improving infrastructure, software quality, testability, maintainability and reliability

CI/CD ownership: Own and evolve our shared GitHub Actions platform so it stays maintainable, reliable and easy to adopt across the team's repositories. Our stack is mainly Python, so you'll need a solid grasp of the Python packaging and tooling ecosystem. Occasionally you'll extend the platform to...

• Build and own scalable data pipelines and integration solutions our data warehouse and data platform.
• Integrate and transform data from ERP, CRM, finance, and other enterprise systems.
• Ensure high standards of data quality, reliability, performance, and operational excellence.

Building efficient and scalable ETL/ELT processes to ingest, transform, and load data from various structured and unstructured sources (databases, APIs, streaming platforms) into BigQuery and Cloud Storage...

• Evaluate, configure, and maintain the AI development tool stack (GitHub Copilot, custom agents, local LLMs).
• Standardise how AI agents interact and integrate with our internal tools, services, and development workflows with MCP.

• Build and contribute to cloud-native software applications and developer tooling.
• Explore modern technologies across artificial intelligence, AI agents, mobile development, and cloud platforms.
• Automate development workflows to make software and product development faster, simpler, and more reliable.

• Design, deploy, and maintain scalable on-premise infrastructure,
• Implement Infrastructure as Code (IaC) using Terraform, Ansible, or similar tools,
• Ensure high availability, resilience, and security of on-premise environments.
• Develop and maintain automated CI/CD pipelines for application deployment,

• Develop, maintain and optimize Python and Linux shell scripts for data extraction, transformation, and loading.
• Build automated pipelines and reusable code modules to support recurring reporting and analytics workloads.
• Ensure accuracy, completeness, and consistency of datasets.

• Develop, maintain and optimize Python and Linux shell scripts for data extraction, transformation, and loading.
• Build automated pipelines and reusable code modules to support recurring reporting and analytics workloads.
• Ensure accuracy, completeness, and consistency of datasets.

Predictive ML: Build models for lead generation, demand forecasting, residual value forecasting, portfolio steering, and fraud detection....

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

Your responsibilities will encompass overseeing the launch of the ESC in 2025, working closely with global AWS teams, and influencing the evolution of AWS services and technology. A typical day in this role involves collaborating with technology leaders, contributing to the enhancement of...

• As a Working Student AI Research Engineer for SLM Optimization (m/f/d/x), you will support the team in developing, refining, and managing caching mechanisms for Small Language Models (SLMs).
• You will contribute to the training and further development of models for cache prediction.

You architect cloud and hardware solutions to scale AI workloads across GPUs and accelerators, while optimizing storage and networking for throughput, resilience, and cost efficiency....

• Development of mathematical models to describe cellular dynamics
• Implementation of the models in a suitable programming environment
• Simulation of cellular dynamics within complex 3D structures
• Application of the computer model as a virtual bridge between in vitro and in vivo studies

• Development and implementation of interfaces between clinical data sources, medical knowledge bases, and local LLM/agent-based systems
• Development of high-performance data pipelines for loading, structuring, validating, and further processing interoperable health data

• Owning the technical architecture on cloud and platform programmes from design through to production, across AWS and Azure.
• Leading engineering teams on delivery, typically three to eight engineers, through mentoring, code review and technical decision making rather than line management.

Work in our Data & AI Center of Excellence (DACE) in close collaboration with a diverse team of 45 data scientists and AI engineers from various disciplines...

• Design and build AI agents and workflows that solve concrete business problems
• Take technical ownership of applied AI solutions - from architecture decisions to engineering standards and code quality
• Build enterprise-grade solutions on modern AI platforms, mainly Azure

• The data platform end to end: ingestion, storage, and the query paths that keep millions of records fast on screen. You design it, you build it, you run it in production.
• The platform layer, directly with the CTO: infrastructure, deployments, and the path to production for the whole team.