Python programozó diákmunka állások, munkák it programozás, fejlesztés területen

• collaborating on the design and development of ML‑based applications and their backend components
• helping to select the most applicable solutions for a given business problem
• writing clean, efficient and well‑documented code
• contributing to our MLOps processes

• Az integrált vállalatirányítási rendszer fejlesztésének és működtetésének szakmai irányítása; az ehhez kapcsolódó IT projektek tervezésének, megvalósításának és szabályozási kereteinek kialakítása
• Aktív részvétel a vállalatirányítási rendszerek továbbfejlesztésében, fejlesztési irányok meghatározása

• Architect and lead the development of large-scale ML systems and model pipelines
• Introduce new ML systems such as traffic sign detection, building facade detection, and other computer vision-based solutions
• Define and drive the ML technical roadmap in alignment with company objectives

• Development, governance, deployment, and enhancement of liquidity analytics models and supporting infrastructure across asset classes
• Driving the analytics product lifecycle including prioritization, roadmap influence, and deployment into production

• Resource account igénylése és összekötése namespacekkel
• Resource accountba kerülő komponensek megvalósítása RDS, APIk, S3, MSK, cognito, SES, private link endpoint és endpoint service nonprod és prod környezeteken
• RICE API kapcsolatok kialakítása

• Design, build, and operate the firm’s AI platform including shared services, APIs, SDKs, and tooling
• Drive architecture across scalability, reliability, security, developer experience, and cost

Technical and business support for GSCF applications supporting daily operations, fund accounting, financial reporting, and data processing functions...

• Build and evolve CI infrastructure that validates performance methodologies across cloud, on-prem, and hardware targets
• Design controlled, reproducible test environments that help distinguish real regressions from environmental noise when running and profiling targeted workloads

• Shape and implement the company’s data science strategy and drive innovation, with a primary focus on Generative AI and Agentic workflows
• Identify opportunities to leverage data for business value and impact
• Take ownership of the full technical stack for development and deployment

• Lead implementation of AI, GenAI, ML, automation, and AI-powered applications.
• Translate solution designs and requirements into development plans and working software.
• Drive engineering delivery aligned with the target architecture.

Development and enhancement of the MSCI Index Development Platform and the IndexMetrics Real-Time application using modern software engineering practices, Python, Azure, and AI-assisted development tools...

• Be able to manage small teams to deliver analytic functions in support of strategic and business development projects.
• Analyse and assess macroeconomic, energy market and other industry-specific developments by synthetizing available empirical evidence, related literature, and economic theory.

• Design and implement data fabric architecture across heterogeneous data sources and platforms
• Develop scalable ETL/ELT pipelines for batch and real-time data integration
• Integrate structured and unstructured data from databases, APIs, SaaS applications, data lakes, and enterprise systems

• Active involvement in the software design and test of reference application processor firmware
• Low level software development, test and debug on various platforms including software models, development boards and shipping products

• Discovery & Shaping: Lead stakeholder workshops, translate business needs into MVP scopes, and map out scalable implementation roadmaps.
• End-to-End Architecture: Design and document (C4 diagrams, API contracts) robust cloud architectures covering application, data, and LLM layers.

• Development of the Voice AI Agent using Python, LiveKit and WebRTC
• Ownership of end-to-end real-time voice pipelines including streaming ASR/TTS, VAD, diarization, state management, retries and latency optimization

• részvétel a teljes egyetemi adatvagyon központosítását célzó, az egyetem által működtetett adattárház továbbfejlesztésében,
• adattisztítás módszertanának fejlesztése, adatmodellek létrehozása, adatkapcsolatok kialakítása, sématervezés,

• Client-facing communication
• Participation in pre-sales discussions
• Collaboration with sales and customer success teams
• Communication with clients' technical teams
• Solution design and delivery
• Design and configuration of data labeling and processing pipelines using Python-based tools

• AI-eszközök bevezetésében, integrációjában és üzleti környezetbe történő beágyazásában való aktív közreműködés
• Üzleti igények feltérképezése, valamint AI use case-ek üzleti és technológiai megvalósíthatóságának értékelése

• The CloudOps Engineer is responsible for availability for cloud platforms
• Respond, troubleshoot and resolve production alarms
• Communicate and troubleshoot operational issues supporting a complex environment
• Respond to cloud service outages and manage incident tickets