Python developer állások, munkák Budapesten

• Creating the architecture and detailed design of HIL environments for embedded space systems
• Integrating and maintaining HIL environments for embedded space systems
• Integrating hardware components, simulators and software into cohesive systems

• Design and implement pipelines to ingest, clean, and transform data into Data Lakes and Data Warehouses
• Active monitoring and optimization of pipelines for performance and cost
• Configuration of pipeline deployments and management of environment settings using IaC tools and CI/CD

• Komplex AI megoldások fejlesztése ügyfelek számára
• RAG alapú megoldások fejlesztése Python/LangChain vagy Java/Spring AI technológiákkal
• Open source LLM-ek integrálása ügyfélrendszerekbe cloud és on-premise környezetben Kubernetes használatával

• Further development of existing optimization components of the airline management system Netline/Crew or Netline Scheduling area
• Implementation and experimentation on new and efficient optimization approaches
• Recording customer requirements for the commissioning of existing optimization components

• Build and maintain scalable cloud infrastructures using modern services and best practices
• Proactive detection, analysis, and fixing of vulnerabilities and performance bottlenecks in cloud environments

• Design and implement enterprise-scale data pipelines and advanced analytics dashboards
• Develop and optimize data ingestion, transformation, and modeling workflows across structured data environments and cloud-based platforms

• CI/CD-folyamatok tervezése, felépítése és üzemeltetése (Azure DevOps, GitLab CI, GitHub Actions vagy Jenkins)
• Infrastruktúra kezelése kód formájában (Terraform, Bicep/ARM, Ansible)
• Konténeres környezetek felépítése és üzemeltetése (Docker, Kubernetes / AKS)

• Data ingestion processes from various sources into the Data Lake
• Design, development and optimization of complex data pipelines for reliable data flow
• Build, development and maintenance of frameworks facilitating construction of data pipelines

• Analysis of system requirements from a verification point of view
• Support of breakdown activities and creation of lower tier requirements
• Planning, defining, and maintaining system and subsystem verification strategy in collaboration with system engineers and project managers

• Lead the design and implementation of scalable data pipelines and Lakehouse architectures
• Act as the design authority
• Solve the hardest technical challenges including optimizing high-load streaming pipelines, debugging complex Spark jobs, and designing generic frameworks

Support of routine daily activities for system design, build, testing, validation, maintenance, and ongoing support of all network infrastructure components...

• Experience in different data science topics
• Independent delivery of data science projects with e2e product-oriented mindset
• Direct engagement with clients to understand business objectives and translate into technical requirements
• Leading pre-sales technical discussions

• Technical onboarding of TelCo and OSS applications onto Kubernetes-based platforms
• Contribution to Site Reliability Engineering through automation of operational tasks and creation of enhancements

• Analysis of webshop and digital campaign performance across multiple brands and channels
• Building and maintaining campaign benchmarking databases using historical performance data
• Development of forecasting methodologies and performance estimates for future campaigns

• Build and maintain dataset ingestion, cleaning, and versioning pipelines
• Design and operate labeling workflows including quality control and inter-annotator agreement tracking
• Own dataset testing including coverage analysis, class balance, leakage detection, and dataset documentation

• Integration of security best practices into the DevOps lifecycle
• Implementation and continuous improvement of security services, CI/CD pipelines, and cloud infrastructure with focus on automation and scalability

• Design, build, and operate enterprise-grade Agentic AI platforms
• Own architecture and delivery
• Mentor engineers
• Partner closely with client and internal teams
• Run secure AI environments at scale under strict regulatory and security requirements
• Architect Zero-Trust environments for LLM-based solutions

• Leadership in integration of security best practices into DevOps lifecycle
• Architecting, implementing, and continuously improving security services, CI/CD pipelines, and cloud infrastructure
• Design and enforcement of secure configuration management, secrets handling, RBAC, and network policies

• Training and fine-tuning models against curated datasets
• Running systematic hyperparameter and architecture experiments
• Building and maintaining evaluation suites including regression tests for model behavior and benchmark tracking

• Design and develop scalable cloud security automation solutions across multi-cloud environments
• Build and maintain platform services using modern engineering practices and a code-first approach
• Own and enhance CI/CD pipelines that enable secure, reliable and efficient delivery