Python állások, munkák Törökbálinton

• Research, develop, implement, and test artificial intelligence algorithms to improve the quality and robustness of the static world model in automated vehicles
• Focus on road structure including lanes, curbs, and drivable trajectories

• Use formal verification algorithms to formally prove the correctness of complicated logic problems
• Identify key behaviors for verification to write clear testplans for complex designs
• Implement testplans using innovative formal techniques
• Drive tools to realize their best performance

• Lead annual and periodic User Developed Application (UDA) assessments and certifications, ensuring compliance with bp controls and regulatory requirements
• Partner with participants, application owners and technical teams to identify, assess and remediate control gaps, reducing risk

• Kutatás-fejlesztési projektek végigkövetése a tervezéstől az átadásig
• Beágyazott vezérlők programozása C nyelven
• Prototípus berendezések beüzemelése
• Prototípus berendezések tesztelése
• Belsős és partner cégek villamos-, programtervező-, gépész-, és mechatronikai mérnökeivel való együttműködés

• Üzletkritikus alkalmazások napi üzemeltetése és monitorozása
• Incidensek, hibajegyek kezelése, root cause elemzés
• Élesítések, release-ek és patchelések végrehajtása
• Linux/Unix rendszerek, Oracle adatbázisok és alkalmazásszerverek üzemeltetése
• AWS és OpenShift környezetek támogatása

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• 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

• Trade a wide range of financial instruments
• Develop, maintain, and improve trading strategies and algorithms
• Run trading desks and support day-to-day trading operations
• Manage execution and risk across complex trading portfolios
• Analyze market data and identify opportunities for strategy improvement

• Development and refinement of core sports betting models for predicting match outcomes
• Building and maintenance of player statistics models analyzing player performance
• Design and implementation of risk management models to optimize exposure

• Design, build and deploy LLM-powered pipelines and autonomous agents
• Scope and deliver AI solutions in collaboration with stakeholders
• Set best practices around MLOps and production-grade AI
• Mentor developers and contribute to internal knowledge-sharing

• Design and update of data architecture to ensure a managed and automated process for data flows
• Optimization of data platforms (PostgreSQL) to ensure stable and timely data streams
• Building and continuous optimization of data ETL (Extract, Transform, Load) processes

• Definition and improvement of metrics reflecting product performance, service quality, and operational efficiency
• Analysis of client behavior and service processes to identify trends, bottlenecks, inefficiencies, and drivers of performance

• 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

• Development and optimization of algorithmic trading systems
• Writing clean, high-performance code in C++ or Rust
• Collaboration with engineers and quants to deliver robust, scalable trading infrastructure
• Contribution using Python for scripting or tooling tasks

• Design, build and deploy LLM-powered pipelines and autonomous agents
• Scope and deliver AI solutions with stakeholders
• Work with frameworks like LangChain
• Set best practices around MLOps and production-grade AI
• Mentor developers
• Contribute to internal knowledge-sharing

• Preparing journey to containerization
• Improving delivery via cloud deployment
• Increasing scalability of systems
• Maintaining high quality of systems
• Re-evaluating systems design
• Working on new features
• Supporting development teams (Backend and Frontend focused)
• Enhancing CI/CD pipelines

• Design and build scalable, reusable frameworks and services for data ingestion, transformation, and processing
• Develop and maintain the platform’s core capabilities such as orchestration, data quality validation, and schema management tools

• 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

• Architect cloud-native AI applications integrating LLMs, vector search, and real-time data
• Design end-to-end web solutions from frontend to backend
• Implement RAG pipelines, model serving, and AI agents in production
• Lead cross-functional teams (Full-stack, AI, Data)

• Technikai menedzsment és fejlesztés a csapat felhőalapú adatplatformján és adatmodellein Azure Databricks környezetben
• A Data-Driven Project Modelling (DPM) motor fejlesztése és karbantartása DevOps legjobb gyakorlatok szerint
• Üzleti logika adatmegoldássá történő átalakítása multinacionális csapatban