Python programozó diákmunka állások, munkák

• 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

• Manage day-to-day cash flows and ensure liquidity for operational and investment needs
• Prepare short-term liquidity forecasts in close collaboration with the investment team, including capital calls and distributions

• 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

• Measuring performance of multi-channel patient recruitment campaigns
• Optimizing multi-channel patient recruitment campaigns
• Forecasting performance of patient recruitment campaigns
• Translating recruitment data into actionable insights
• Accelerating enrollment in clinical trials

• Design and run Kubernetes environments optimized for AI inference, retrieval, experimentation, and agent execution in secure or isolated settings
• Deploy and operate open-source or open-weight model stacks, model gateways, vector databases, and supporting platform components

• Design, implement, and operate resilient IT infrastructure across on-premise and cloud environments (Azure/AWS)
• Ensure high availability, performance, and reliability of systems through proactive monitoring and optimization

• 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

Design, train, and evaluate machine learning models for manufacturing use cases such as quality prediction, anomaly detection, predictive maintenance, and process optimisation, covering the full ML lifecycle from problem definition to performance tuning....

• Design, development, and optimization of core ML models, especially in computer vision and deep learning
• Development of efficient, scalable training and inference pipelines
• Mentoring junior ML engineers, reviewing code 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

• On-premise IT infrastruktúra üzemeltetése, támogatása és folyamatos fejlesztése
• Linux alapú rendszerek adminisztrációja
• Kubernetes klaszterek adminisztrációja
• Middleware komponensek adminisztrációja
• Automatizációs feladatok megvalósítása és karbantartása

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

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

• Definition and improvement of metrics representing product performance and operations efficiency
• Data collection from multiple sources ensuring accuracy and completeness
• Data cleaning, organization, and transformation into usable formats for analysis

Develop next-generation discrete ESD and TVS protection devices for high-speed, RF sensitive and automotive applications....

• Design of network solutions within a Juniper Hybrid WAN (Spine-Leaf) environment
• Implementation of network solutions within a Juniper Hybrid WAN (Spine-Leaf) environment
• Optimization of network solutions within a Juniper Hybrid WAN (Spine-Leaf) environment