Python állások XVIII. kerületben (ai és automatizáció)

• Design, develop, review, and test features and user stories following Agile development practices
• Contribution to core platform development and integration projects across multiple systems
• Shaping the future architecture of the product including designing scalable backend services and prototypes

• Kereskedelmi és ipari szektorban dolgozó ügyfelek digitalizációs problémáit megoldó zöldmezős webes applikációk és mobil app-ok backend fejlesztése
• Szoftverek teljes architektúrális tervezésében és kialakításában való részvétel senior jelölt esetén

• Design, develop, deploy, monitor, scale, and troubleshoot ML and LLM-based systems that power shared AI services across the platform
• Build secure, high performance microservices and platform components on AWS, owning services end-to-end from implementation through deployment and production monitoring

• Design and implement automation for storage provisioning, capacity management, and operational workflows using Python, Bash, and IaC tooling
• Drive reduction of manual toil through scripted workflows and self-service enablement

• Design, implement, and optimize machine learning models to solve complex business problems
• Oversee the entire machine learning lifecycle, from data collection and pre-processing to model deployment and monitoring

• Design and implement data models aligned with industry best practices
• Build and optimize scalable data warehousing and lakehouse solutions and ensure data integrity end-to-end
• Create and own robust ELT pipelines connecting multiple internal and external data sources

Assess and document downstream impact of Skills and Job Architecture data quality issues across payroll processing, management reporting, third-party integrations, and AI/machine learning model inputs...

• Writing reusable, testable, and efficient code mainly in Python
• Delivering great user experience by the development of great user interfaces
• Handling security and data protection professionally and precisely
• Providing technical solutions and implementing new software features collaboratively

• Writing reusable, testable, and efficient code mainly in Python
• Delivering great user experience by the development of great user interfaces
• Handling security and data protection professionally and precisely
• Collaborative work to provide technical solutions and implement new software features

• Developing scalable library software using modern tools and languages for various numerical method
• Performance tuning, optimization, and benchmarking of algorithms on various architectures

• 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

• 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

• Az Agentic AI Platform vállalati integrációs rétegének kialakítása és továbbfejlesztése.
• MCP-szerverek és connectorok fejlesztése és üzemeltetése, amelyek szabványosított és szabályozott hozzáférést biztosítanak az AI-agentek számára a vállalati rendszerekhez és eszközökhöz.

• 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

• Ügyfeleink felhasználóinak támogatása (helpdesk, távoli és helyszíni support, GLPI jegykezelés)
• Windows kliens- és szerverkörnyezetek, Active Directory és Entra ID üzemeltetése, hibaelhárítás
• Microsoft 365 és Intune adminisztráció (felhasználók, licencek, eszközkezelés)

• 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 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

• Design and implement automated test cases for backend, frontend, or API-based systems
• Collaborate with distributed teams across multiple time zones
• Participate in requirement analysis to ensure testability and clarity

• The CloudOps Engineer is responsible for availability for cloud platforms
• Respond, troubleshoot and resolve production alarms
• Communicate and troubleshoot operational issues supporting a complex environment
• Respond to cloud service outages and manage incident tickets

• 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