Python állások, munkák II. kerületben

Working on the design, development, and production of advanced digital solutions, ensuring seamless integration with existing infrastructure and adherence to enterprise architecture standards and robust delivery lifecycle processes. This includes leveraging expertise in various digital technologies...

• Learning from senior team members
• Participation in security penetration testing projects including application-level penetration testing (e.g., web application, Android, or iOS Mobile application)
• Participation in infrastructure level security penetration testing
• Participation in Red Teaming

• 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

• nagy mennyiségű adat feldolgozását támogató adatfolyamatok tervezése és fejlesztése,
• adatbetöltési, adattranszformációs és adatminőség-ellenőrzési folyamatok kialakítása,
• adatforrások integrálása, strukturált és félig strukturált adatok kezelése,

• 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 optimization of large-scale data processing workflows using Apache Spark, PySpark, and SQL
• Building and enhancing multi-stage ETL pipelines with idempotency and failure recovery
• Implementation and configuration of pipeline orchestration using Airflow, Dagster, or Prefect

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

• 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 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

• 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 and contribute to internal knowledge-sharing

• 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 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 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

• 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

• 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

• 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)

• Design, develop, and maintain multimedia middleware components
• Build, integrate, and optimize GStreamer-based audio/video pipelines
• Integrate media components with user-space applications and system services
• Debug and resolve complex media issues related to performance, stability, and synchronization

• Preparation for containerization and cloud deployment
• Increasing scalability of systems
• Re-evaluation of systems design and development of new features
• Support for development teams (Backend and Frontend)
• Enhancement of CI/CD pipelines
• Improvement of monitoring and observability

• 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