Python állások XIV. kerületben (it programozás, fejlesztés)

• 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

• 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

• Maintaining and evolving data structures
• Building new ETL flows and maintaining or improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods

• Elosztott rendszerek, mikroszervizek és felhőalapú infrastruktúrák teljes körű observability-jének kiépítése
• Teljesítmény, elérhetőség és stabilitás javítása cutting-edge eszközökkel és módszertanokkal
• Nagyvállalati környezetben előforduló problémák feltérképezése, hibakeresés és dokumentáció

• 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, 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

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

• Komplex AI megoldások fejlesztése ügyfelek számára
• RAG alapú megoldások fejlesztése Python/LangChain vagy Java/Spring AI technológiákkal
• Open source LLM-ek integrálása ügyfélrendszerekbe cloud és on-premise környezetben Kubernetes használatával

• 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

• 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

• Design and implement backend services and APIs
• Develop new features together with Product Owner and Architects
• Optimize performance, scalability and security
• Write unit and integration tests
• Review merge requests and ensure coding standards
• Troubleshoot incidents and perform root cause analysis

• 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

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

• 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

• Development of native Android applications
• Design of user interfaces and functions as planned
• Participation in the definition of requirements and estimation of tasks
• Writing Unit and UI tests and participation in developer testing
• Staying up-to-date with current technology trends in Android development