Python állások I. kerületben középiskolai végzettséggel

• Design, build, and maintain robust CI/CD pipelines
• Manage and optimize cloud infrastructure on T Cloud Public, ensuring high availability and performance
• Administer and troubleshoot Linux and Windows systems in production environments

Development and enhancement of the MSCI Index Development Platform and the IndexMetrics Real-Time application using modern software engineering practices, Python, Azure, and AI-assisted development tools...

• Implementation and improvement of business objects for mobile network infrastructure in backend systems up to the API layer
• Development and maintenance of business objects including data models, backend logic, and APIs

• Writing clean, maintainable Python code and automation scripts (bash/shell)
• Building CI/CD pipelines and deployment automation for AI systems
• Creating infrastructure as code and configuration management solutions (terraform)
• Developing APIs, microservices, and event-driven architectures

• Leading, mentoring, and empowering a team of ML engineers
• Owning model quality end-to-end from experimentation to production-ready artifact
• Conducting regular 1-on-1s for career development and feedback
• Removing blockers and ensuring team well-being

• Definition and development of system-level tests for high-end embedded computing systems
• Automation of test execution and evaluation through scripting in a CI environment
• Increase of test coverage by extending functional examples into comprehensive test suites

• Design, develop, and maintain automated test suites as code using Java
• Create BDD-based automated test scenarios using Cucumber against REST APIs
• Automate API testing for OAuth 2.0 and OpenID Connect (OIDC) authentication and authorization flows using RestAssured or similar tools

• Software release delivery on schedule with defined scope and quality
• Transition to continuous delivery
• Reliable operation of CI/CD pipelines
• Improvement of CI/CD pipeline efficiency
• Contribution to test strategy
• Coordination of test strategy execution
• Development of test frameworks and automation tools

• 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, dataset documentation

• Tackling complex technical challenges focused on scalability, reliability, and speed
• Maintaining a high-performance infrastructure that processes millions of events with low latency
• Collaborating with Data Scientists and Engineers to design and implement cutting-edge feature topologies

• Architect cloud-native AI applications integrating LLMs vector search and real-time data
• Design end-to-end web solutions from frontend to backend
• Implement RAG pipelines model serving and AI agents in production
• Lead cross-functional teams (Full-stack AI Data)

• Training and fine-tuning models against curated datasets
• Running systematic hyperparameter and architecture experiments
• Building and maintaining evaluation suites
• Analyzing model failures and translating findings into dataset or training improvements

• Improvement of repetitive processes
• Organization, cleaning and analysis of data
• Automation of everyday tools and processes
• Experimentation with AI tools, chatbots and workflows
• Troubleshooting and operational task support
• Data verification and follow-up to ensure process compliance

• 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

• Technikai menedzsment és fejlesztés a csapat felhő alapú adatplatformján és adatmodellein Azure Databricks környezetben
• A Data-Driven Project Modelling (DPM) motor fejlesztése és karbantartása DevOps legjobb gyakorlatok szerint
• Üzleti logika adatmegoldássá történő átalakítása multinacionális csapatban

• Administration and support of enterprise DNS, DHCP and IPAM services using CygnaLabs QIP
• Management of DNS zones and DNS records (A, AAAA, CNAME, PTR, MX, TXT, SRV)
• Configuration and maintenance of DHCP scopes, reservations, exclusions, options and lease management

• Architect cloud-native AI applications integrating LLMs, vector search, and real-time data
• Design end-to-end web solutions from frontend to backend
• Implement RAG pipelines, model serving, and AI agents in production
• Lead cross-functional teams including Full-stack, AI, and Data

• Resource account igénylése és összekötése namespacekkel
• Resource accountba kerülő komponensek megvalósítása RDS, APIk, S3, MSK, cognito, SES, private link endpoint és endpoint service nonprod és prod környezeteken
• RICE API kapcsolatok kialakítása

Eszköz-Forrás Menedzsment (ALM) területen alkalmazott likviditási és banki könyvi kamatlábkockázati modellek, módszertanok fejlesztésében való részvétel hazai és nemzetközi környezetben....

● Audiovizuális megoldások (Digital Media Signage, videókonferencia rendszerek) támogatása és tesztelése ● Ügyfélprojektekhez kapcsolódó integrációs fejlesztésekben való közreműködés ● Ügyféldemók és technikai bemutatók összeállítása, karbantartása ● Rendszerüzemeltetési és monitoring feladatok...