Python programmer állások, munkák XIV. kerületben

• Banki környezetben lévő java alkalmazásszerverek (Welogic, Glassfish, Websphere) napi működésének feltételei biztosítása (performancia, üzembiztonság, mentések, monitorozás)
• Weblogic, Glassfish és Websphere alkalmazásszerverek folyamatos üzemeltetése és monitorozása

• 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

• Development of the Voice AI Agent using Python, LiveKit and WebRTC
• Ownership of end-to-end real-time voice pipelines including streaming ASR/TTS, VAD, diarization, state management, retries and latency optimization

• Design, implement, and operate IT infrastructure across on-premise and cloud environments (Azure)
• Ensure high availability, performance, and reliability of systems through proactive monitoring and optimization

Performing tasks related to the position....

• Development and optimization of large-scale data processing workflows using Apache Spark, PySpark, and SQL
• Building and enhancing multi-stage ETL pipelines with idempotency and failure recovery
• Implementation and configuration of pipeline orchestration using Airflow, Dagster, or Prefect

• Contribution to the ID Verification ML team building in-house ML solutions
• Delivery of high-quality NodeJS, TypeScript and Python code with simplicity, performance and scalability in mind

• Definition and improvement of metrics reflecting product performance, service quality, and operational efficiency
• Analysis of client behavior and service processes to identify trends, bottlenecks, inefficiencies, and drivers of performance

• 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

• Design, build and deploy LLM-powered pipelines and autonomous agents
• Scope and deliver AI solutions with stakeholders
• Work with frameworks like LangChain
• Set best practices around MLOps and production-grade AI
• Mentor developers
• Contribute to internal knowledge-sharing

• Development and refinement of core sports betting models for predicting match outcomes
• Building and maintenance of player statistics models analyzing player performance
• Design and implementation of risk management models to optimize exposure

• Design and implement data fabric architecture across heterogeneous data sources and platforms
• Develop scalable ETL/ELT pipelines for batch and real-time data integration
• Integrate structured and unstructured data from databases, APIs, SaaS applications, data lakes, and enterprise systems

• Creation and preparation of 3D assets, environments, and scene layouts for Omniverse and OpenUSD workflows
• Assembly of digital-twin scenes for industrial, facility, product, or enterprise visualization use cases

• Design, build and deploy LLM-powered pipelines and autonomous agents
• Scope and deliver AI solutions with stakeholders
• Work with frameworks like LangChain
• Set best practices around MLOps and production-grade AI
• Mentor developers
• Contribute to internal knowledge-sharing

• Design and build learner models including knowledge tracing and longitudinal approaches
• Shape the data foundation for learner modeling by defining relevant signals and building datasets
• Translate mastery and progression definitions into model targets and evaluation criteria

• Ownership of data models and storage architecture behind AI systems across relational, graph, and retrieval-oriented data
• Building and operating APIs, backend services, and pipelines to keep data current and accessible

• End-to-end AI solution ownership from problem definition through prototype validation and production support
• Partnership with product managers and business stakeholders to translate real-world problems into data science and AI initiatives

• CI/CD pipeline-ok kialakítása, fejlesztése és karbantartása
• Deployment és release folyamatok automatizálása
• Cloud infrastruktúrák üzemeltetése és optimalizálása
• Konténerizált környezetek kezelése (Docker, Kubernetes/OpenShift)
• Monitoring, logging és alerting rendszerek kialakítása és üzemeltetése

• Üzleti igények összegyűjtése és elemzése
• IT rendszerek és szoftverek elemzése
• Fejlesztési igények meghatározása
• Funkcionális és technikai specifikációk készítése
• Üzleti célok és IT megoldások közötti összhang biztosítása
• Szoftverfejlesztési életciklusban való aktív részvétel

• Support the Python development process
• Contributing to the successful execution of customer projects
• Engage in rigorous testing of code and applications to ensure quality and performance
• Participate actively in the DevOps team activities including daily calls and project-related communications