Maneger állások XVIII. kerületben (programozó, fejlesztő)

• Triaging new requirements, assessing their impact, and providing estimates for modifying data models accordingly.
• You will also be responsible for developing and enhancing business physical data models to meet evolving needs while driving alignment as necessary.

• Build the team’s skillset while demonstrating your leadership values through delegation, motivation and trust. You will not just lead, but "do".
• Contribute to digital transformation initiatives from an architectural perspective, facilitating the delivery of solutions.

Integrating delivered components into working embedded systems Debugging firmware, drivers, and application-level issues Adapting and extending example code and reference designs Building internal demos and proof-of-concept applications Giving structured, technical feedback based on real usage...

Implement and maintain large‑scale data pipelines and the Azure/Databricks data platform in close collaboration with the Architect, contributing to design discussions and proposals. Build robust, scalable pipelines using Azure Databricks (PySpark / SQL), integrating data ingestion, processing,...

Leading a high-performing team of 3 to 8 engineers Working across the complete software lifecycle, including requirements, planning, development, release and support and maintenance Developing Linux device drivers and exposing these to application software...

Develop highly scalable services realizing AI/ML functionalities (e.g. NLP, ML and AI models) Implement various machine learning solutions addressing computer vision and NLP use cases Work with Large Language Models (LLMs), perform prompt engineering tasks Design and implement data transformation...

Lead and Cultivate Engineering Talent: Provide direct line management, coaching, and career development for a team of Full-Stack Engineers. Provide Hands-On Technical Leadership: Serve as the dedicated Solutions Architect and technical lead on our most strategic and complex cloud-native application...

• Megbízható, valós idejű szoftverrendszerek fejlesztése és karbantartása
• Új funkciók tervezése, fejlesztése és tesztelése
• Autonóm navigációs algoritmusok implementálása
• Szenzoradatok feldolgozása, szenzorok és rendszerelemek integrációja

Implement and maintain large‑scale data pipelines and the Azure/Databricks data platform in close collaboration with the Architect, contributing to design discussions and proposals. Build robust, scalable pipelines using Azure Databricks (PySpark / SQL), integrating data ingestion, processing,...

Design, implement, and manage Azure cloud infrastructure to support Databricks and data platform workloads Build and maintain Azure resources including Resource Groups, VNets, Key Vaults, Storage Accounts, and Azure Active Directory (AAD) integrations Implement Infrastructure as Code (IaC) using...

Collaborate on various full-stack F# web projects Attend regular online status and team calls and/or face-to-face meetings Help your team deliver each iteration on-time and successfully...

• Üzleti igények technikai specifikációvá alakítása
• Technikai tervezés, architektúra kialakítása
• Technológiai irányelvek és architekturális standardek kialakítása és fenntartása
• Feladatok meghatározása a projektmenedzserrel együttműködésben
• Kódellenőrzés (code review), fejlesztések minőségbiztosítása

Programming in languages relevant to AI (e.g., Python, Java) Using modern AI/ML frameworks and platforms (e.g., TensorFlow, PyTorch, Oracle Cloud AI services) Enterprise software development including REST APIs, microservices, and cloud-native architectures Translating business needs into scalable...

Design and develop cloud-native application services on Kubernetes using Java, Python, and Spring Boot Integrate application components with OCI services, including GenAI Service, Object Storage, and API Gateway Implement AI-powered capabilities using LLMs, prompt engineering, and agentic...

Design, train, and optimize machine learning models for real-world applications. Build end-to-end ML pipelines including data preprocessing, feature engineering, model training, validation, and deployment. Collaborate with data engineers and software developers to integrate ML models into...

Translating business needs into scalable AI solutions Developing enterprise-grade AI solutions Working effectively in a collaborative, multi-disciplinary, and global team environment...