Programozó állások, munkák

• Fejlesztési folyamatok támogatása DevOps eszközökkel
• Központi, integrált CI/CD megoldás támogatása és fejlesztése, valamint új projektek bevonása
• Együttműködés az infrastruktúra üzemeltetéssel
• Projektalapú együttműködés fejlesztőkkel, üzleti elemzőkkel és ügyfelekkel

• Dotnet alkalmazások fejlesztése és karbantartása C# és .NET Core technológia használatával
• RESTful API-k és mikro-szolgáltatások fejlesztése
• Adatbázisok kezelése és optimalizálása
• Szoftverek teljesítményének javítása és hibák keresése
• Meglévő kódok refaktorálása

• Designing and developing backend services and APIs that support real-time data ingestion, transformation, and delivery
• Building scalable, low-latency, high-throughput systems capable of handling demanding performance requirements

• Data entry of unstructured property data
• Creation of new databases with defined collection criteria and quality standards
• Definition and setup of KPIs for data accuracy and completeness
• Assistance with ad-hoc data and analysis requests

• Teljes körű kontrolling rendszer kialakításában és működtetésében aktív részvétel
• Stratégiai és operatív tervezés, üzleti terv készítés, szoros együttműködés a társosztályok vezetőivel
• Üzleti területek eredményének nyomon követése, terv/tény elemzések, eltérés analízis kidolgozása

• 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

• Writing production-quality, well-tested scraper code in Python
• Learning the architecture of the collection platform including scrapers, proxy layer, queues and enrichment API
• Debugging issues across multiple components using logging, monitoring and alerting tools

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

What awaits you? • Work environment – you work on-site at the BMW Group Plant Debrecen in the Assembly area, located in the Production Office. You will collaborate closely with production and business teams in a modern and digitalized manufacturing environment, supporting daily operations and...

• Client-facing communication
• Participation in pre-sales discussions
• Collaboration with sales and customer success teams
• Communication with clients' technical teams
• Solution design and delivery
• Design and configuration of data labeling and processing pipelines using Python-based tools

• Leading engagements to build and productionize tailored AI applications in the Databricks platform
• Owning the technical delivery of AI solutions independently or as Delivery Technical Lead
• Leading technical scoping and designing high-level architectures for AI and Generative AI solutions

• Development and support of backend applications
• Documentation and testing
• Connection and integration with external systems through APIs

• 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

• Managing complex database systems within a global technology ecosystem
• Building and managing database hosting capabilities using Infrastructure as Code for all platform needs
• Building database infrastructure platforms with developers and providing guidance and tooling to handle distributed systems

• in vitro sejtes és in vivo állatkísérletes ill. az ezekhez kapcsolódó molekuláris biológiai, biokémiai és farmakológiai vizsgálatok;
• sejttenyésztés, klónozás, transzfekció, PCR és génexpressziós vizsgálatok;
• fehérje- és DNS-tisztítás, immunhisztokémiai és egyéb laboratóriumi módszerek;

• Understanding new Arm architecture and IP features and their implementation
• Devising promotion of benefits to software ecosystems and resolving adoption issues
• Analysis and deep understanding of software solutions deployed in products, especially major open-source projects such as Linux

• 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

• 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

• Real-time decision making with machine learning for risk assessments
• Ownership of risk infrastructure for Instant ACH in the US market
• Cross-functional collaboration with software engineers, data analysts, and data scientists

• 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