Python developer állások XIV. kerületben (it programozás, fejlesztés)

• Architect and implement scalable AI/ML solutions on Azure or GCP
• Design and build AI solutions for sales use cases such as automated RFP/RFI ingestion, classification, and response generation
• Design and build AI solutions for intelligent document understanding

• Build and maintain scalable, reliable, and secure environment on AWS using Infrastructure as Code tools
• Oversee the deployment, configuration and management of clusters
• CI/CD pipeline development with designing and managing CI/CD pipelines, Infrastructure as Code, and GitOps toolset and skillset

• Design, build, and operate enterprise-grade Agentic AI platforms
• Own architecture and delivery
• Mentor engineers
• Partner closely with client and internal teams
• Run secure AI environments at scale under strict regulatory and security requirements
• Architect Zero-Trust environments for LLM-based solutions

• Technical onboarding of TelCo and OSS applications onto Kubernetes-based platforms
• Contribution to Site Reliability Engineering through automation of operational tasks and creation of enhancements

• Integration of security best practices into the DevOps lifecycle
• Implementation and continuous improvement of security services, CI/CD pipelines, and cloud infrastructure with focus on automation and scalability

• Further development of existing optimization components of the airline management system Netline/Crew or Netline Scheduling area
• Implementation and experimentation on new and efficient optimization approaches
• Recording customer requirements for the commissioning of existing optimization components

• Design, build, and launch AI and generative AI solutions
• Create scalable data pipelines and model deployment workflows
• Develop large-language-model and multi-agent products
• Set up automated testing, deployment, monitoring, and improvement

• Development and fine-tuning of AI models including LLMs, Agentic AI, and Generative AI systems
• Building and deploying robust AI applications and services on cloud platforms
• Design and implementation of efficient AI pipelines from data preparation through model deployment and monitoring

• Development and deployment of AI-powered applications using modern software engineering practices
• Integration of Large Language Models into business solutions
• Building scalable backend services using Python or Node.js
• Development of intuitive user interfaces with React or Angular

-Szkript alapú vasúti folyamatok felülvizsgálata és optimalizálása (Python). -Fejlesztői csapat informatikai automatizálással való támogatása. ...

• Digitalizációhoz kapcsolódó projektek és fejlesztések szakmai támogatása, koordinációja az igény létrejöttétől a projekt lezárásáig
• Ügyféligények és üzleti folyamatok felmérése, elemzése, fejlesztési lehetőségek azonosítása

• Managing and migrating ETL pipelines between various source systems
• Validating pipeline build success and output data quality
• Communicating with business stakeholders and SME's regarding their respective data domain
• Analysing and resolving blockers and issues with ETL pipelines and data discrepancies

• Build and maintain scalable cloud infrastructures using modern services and best practices
• Proactive detection, analysis, and fixing of vulnerabilities and performance bottlenecks in cloud environments

• Design and implement modern data architectures and lakehouse solutions
• Provide technical leadership throughout the project lifecycle
• Collaborate with business stakeholders
• Create effort estimations
• Provide technical expertise during the pre-sales phase
• Mentor 3-6 person project teams

• Chunking and ingestion architecture with deterministic, validation-gated pipelines handling diverse enterprise document types with indexing and contextual enrichment
• Retrieval pipeline with vector search, BM25 hybrid retrieval, RRF re-ranking, embedding model selection and optimisation

• Design, implement, and optimize compiler passes and transformations using LLVM/Clang or GCC
• Build and maintain robust toolchains
• Support new and complex architectures in compiler backends
• Work on architecture-agnostic and IR-level optimizations
• Work on silicon specific optimizations

• Build and maintain simulation environments for mobile robotic perception and navigation
• Develop and integrate robotic behaviours and learning pipelines for reinforcement learning and motion planning in complex outdoor environments

• Ownership of data engineering features, architecture, and code quality
• Design, implementation, and maintenance of Databricks-based data pipelines and workflows
• Building and optimization of ETL/ELT processes using Apache Spark on Databricks

• 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, develop, and implement complex, scalable Lakehouse solutions on the Databricks platform across major cloud environments (Azure, AWS, or GCP)
• Design, build, and optimize modular data pipelines using Delta Lake to ensure data efficiency, reliability, and quality