Python programozó diákmunka állások, munkák programozó, fejlesztő kategóriában

• 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

• You design, implement, and operate automated infrastructure and deployment pipelines supporting our software products in microbial identification.
• You support the full lifecycle of our systems, from infrastructure provisioning and configuration to deployment, monitoring, and continuous improvement.

• Development and enhancement of T Cloud Public platform in a customer-oriented manner
• Solving complex problems in the daily operation of a hyper-scaler's cloud backend
• Hardware-oriented work at the console
• Development and operation of monitoring and quality assurance

• Design, develop, and optimize scalable data pipelines for processing large-scale structured and unstructured data
• Ensure reliability, performance, and scalability of data systems
• Build solutions to handle real-time streaming data from multiple sources

• Architect scalable inference services, APIs, and backend components for model-driven and LLM-powered product features
• Productionize AI and ML workflows with strong MLOps practices
• Define and implement evaluation frameworks for model quality, system reliability, latency, and cost

• Design, build, and ship production retrieval systems
• Own vector store selection and operation including scalability, latency, reliability, cost, and multi-tenant design
• Build and operate indexing and refresh pipelines including chunking, embedding generation, backfills, deletes, and versioned indices

• Design and implement new market links and connectivity tools
• Improve and maintain existing high-load, low-latency C++ applications
• Actively reduce latency to optimize trading performance
• Ensure operational excellence and reliability of systems as they scale

• Design of complex and scalable data solutions on the AWS cloud platform
• Development and implementation of complex and scalable data solutions on the AWS cloud platform
• Design and building of data pipelines to ensure efficiency and reliability
• Optimization of data pipelines

• AI-alapú rendszerek és alkalmazások architektúrájának tervezése és fejlesztése
• Microservice és event-driven architektúrák tervezése és technikai irányvonal meghatározása
• Architekturális döntések meghozatala, beleértve a megfelelő technológiai és tervezési megoldások kiválasztását

• Design, implement, and maintain scalable BI and data processing solutions
• Develop and operate ETL pipelines for customer, booking, and product data
• Integrate data from various file- and REST-based Magenta APIs
• Generate and deliver reports and datasets for multiple downstream consumers

• Providing technical assistance and guidance to data engineering and machine learning community
• Taking ownership of difficult technical problems
• Participating in the vision for data engineering through documents and conversations
• Getting buy-in from stakeholders and leadership

• Design, development, and optimization of core ML models in Computer Vision and Deep Learning
• Development of efficient, scalable training and inference pipelines
• Mentoring junior ML engineers, code review and sharing best practices

• Implementation and improvement of business objects for mobile network infrastructure in backend systems up to the API layer
• Development and maintenance of business objects including data models, backend logic, and APIs

Design and build knowledge tracing and longitudinal learner models that support mastery and progression features surfaced to customers...

• Rendszertervezés
• Hibaanalízis és javítás
• Optimizációs javaslatok kidolgozása és megvalósítása
• Unit tesztek és integrációs tesztek végrehajtása, automatizálása
• Termékfejlesztési folyamat irányítása
• Üzleti és termékcélok megértése, alkalmazások felügyelete

• Design and implement new market links and connectivity tools
• Improve and maintain existing high-load, low-latency C++ applications
• Actively reduce latency to optimize trading performance
• Ensure operational excellence and reliability of systems as they scale

• LLM/GenAI architektúrák és agentek tervezése
• Ügyfelek fejlesztési igényeinek felmérése, átlátása és rendszerezése
• Specifikációk és rendszertervek készítése
• Prototípusok és PoC-ok létrehozása
• AI-megoldások jó gyakorlatai szerinti kialakításában való részvétel

• Build and operate multi-cluster containerized environments across cloud platforms
• Create end-to-end CI/CD pipelines for cloud-native applications and machine learning workloads
• Lead cost-optimization and FinOps initiatives for GPU, storage and data-egress spend

• Új technológiák bevezetése
• Termékfejlesztési igények implementálása
• Rendszertervezés
• Tesztelés
• Dokumentálás
• Kapcsolódó alkalmazás- és interfészfejlesztésekben való együttműködés a társszervezőkkel
• Minőségbiztosítási feladatok támogatása

• Development and operation of data pipelines
• Building data layers in OneDataLake (ODL) Central Data Store Consumer (CDSC)
• Balancing business and IT demands to build modern and efficient pipelines in public cloud environments
• Integration of data preparations into managed processes