Javascript állások XI. kerületben (ai és automatizáció)

Design, build, and maintain large-scale C++ analytics libraries with emphasis on performance, correctness, extensibility, and long-term maintainability in a production environment...

• Részvétel a termékek teljes életciklusában a kutatási és tervezési fázistól a fejlesztésen és tesztelésen át a továbbfejlesztésig
• Képfeldolgozással kapcsolatos algoritmusok kutatása, tervezése és fejlesztése
• Neurális hálózatok és gépi tanulási megoldások kutatása, fejlesztése és optimalizálása

• Üzembe helyezési folyamat koncepciójának kidolgozása a projekthez
• CI/CD folyamat felépítése és üzemeltetése a vonatkozó CI/CD eszközök használatával
• CI/CD szerver adminisztrációja
• CI/CD scriptek előállítása
• Tesztautomatizálási eszközök integrálása a CI/CD folyamatba
• CI/CD eszköztár monitorozása

• Writing and maintaining clean, high-quality, and efficient code that aligns with project specifications using AI tools daily to accelerate delivery
• Executing comprehensive testing and seamless deployment of programs and systems

• Design and own secure, scalable services end-to-end
• Guide technical decisions and evaluate trade-offs across reliability, performance, maintainability, and cost
• Architect and deliver AI and agentic product capabilities including LLM integrations, multi-step agentic workflows and intelligent automation

• Building and optimizing inference pipelines for large-scale model serving
• Working with frameworks like PyTorch, TensorRT, and vLLM to deploy models efficiently
• Implementing and optimizing ML models using techniques such as quantization, kernel fusion, and efficient batching

• Design and propose changes to current data systems including migration paths and modernization strategies for legacy architectures
• Define and evolve the target architecture for data platforms covering ingestion, storage, processing, and consumption layers

• Design and evolve robust cloud-native services and platforms with end-to-end ownership from ideation and prototyping to deployment, monitoring, and iteration
• Influence technical direction without direct authority by identifying architectural pain points and improving engineering standards

• Design, build, and maintain large-scale distributed data systems
• Develop data processing pipelines using technologies such as Spark and streaming solutions
• Work on systems that evaluate and ensure the quality and integrity of large-scale knowledge graphs

• Analysis and research of cloud-native tools and frameworks for Google Cloud Platform solutions
• Support for the T-Systems Public Cloud Product Management Team in building and defining solutions

• Development and enhancement of quantitative financial models
• Application of advanced technologies to real world financial problems
• Keeping up to date with the latest technological trends

• Development of cutting-edge CI/CD pipelines
• Streamlining systematic processes
• Maintenance of core gateways
• Ensuring security and integrity of software assets
• Trying out new technologies to improve and expand know-how
• Participation in cross-functional, international agile team

• Design, build, and own secure, scalable cloud-native services using C#/.NET and AWS
• Lead technical decision-making balancing performance, reliability, security, and cost considerations
• Use AI-powered tools to enhance coding, debugging, testing, and prototyping while ensuring quality and safety

• Building complex financial analysis utilizing Microsoft Excel, Python, Alteryx, KNIME, Power BI & Tableau
• Taking part in significant international transaction projects
• Collecting, researching and analyzing data related to the client’s business operations

• Work with an agile mindset and according to agile methodology
• Collaboration within the team, with other teams in the Domain and Deutsche Telekom, and with software engineers using the cloud platform
• Approach work with a DevOps and continuous improvement mindset

• Design, develop, and maintain backend services and APIs that support scalable cloud and on-prem systems
• Take part in architectural discussions, prototyping, and evaluating technical feasibility
• Optimize, test, and continuously improve system performance and reliability

• Providing technical assistance and guidance to Wise's data engineering and machine learning community
• Taking ownership of difficult technical problems
• Participating in the vision for data engineering through documents and conversations
• Getting buy-in from stakeholders and leadership

• Lead and manage end-to-end IT projects
• Coordinate collaboration between internal teams and external vendors
• Drive alignment between business needs and technical implementation
• Ensure effective integration of solutions into existing IT landscape

• Design, build, and deliver scalable full stack solutions using Angular, TypeScript, C#/.NET, and AWS
• Own features from concept through deployment, monitoring, support, and continuous improvement

• AI-alapú rendszerek és alkalmazások architektúrájának tervezése és fejlesztése
• Microservice és event-driven architektúrák tervezése és technikai irányvonal meghatározása
• Architekturális döntések meghozatala, beleértve a megfelelő technológiai és tervezési megoldások kiválasztását