Python programmer állások XI. kerületben (ai és automatizáció)

• Az üzleti alkalmazások fejlesztéséhez, kiadáskezeléséhez és üzemeltetéséhez kapcsolódó feladatok automatizálása (Gitlab, Gitlab CI, Jenkins, Bitbucket)
• Szoftverfejlesztési folyamatok automatizálása, kódminőség javítása, a fejlesztő csapatok támogatása (SonarQube, ArgoCD, Snyk, Trivy, Nexus)

• HUAWEI cloud Europe DCN maintenance: alarm & incident handling, troubleshooting, service restore
• HUAWEI cloud Europe DCN new buildup and expansion, acceptance
• Develop efficient tools for network maintenance and delivery
• Regular meeting with partners or customers

• Design and write clean, scalable Python code to solve challenging, real-world problems
• Build and maintain APIs and data pipelines using FastAPI, SQLAlchemy, and Pandas
• Support and integrate machine-learning workflows into production systems

• Leading and delivering major projects
• Coordinating release activities
• Analysing test data to support quality improvements
• Supporting software developers in using the platform
• Driving more efficient build and test automated pipelines
• Better controlled use of resources

• Writing reusable, testable, and efficient code mainly in Python
• Delivering great user experience by development of great user interfaces
• Handling security and data protection professionally and precisely
• Providing technical solutions and implementing new software features collaboratively

• Writing reusable, testable, and efficient code mainly in Python
• Mastering the integration of user-facing elements developed by front-end developers with server side logic
• Integration of data storage solutions
• Handling security and data protection professionally and precisely

• Understanding implementation of Fixed Income Derivative Pricing Models written in C++ including yield curve, inflation, FX and volatility derivative models
• Quantitative modeling involving analysis of model output and time-series to define correctness criteria and thresholding measured daily

• Providing technical assistance and guidance to Wise's 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

• Algorithm design and implementation for processing and analyzing sensor data from LiDAR, images, and satellite imagery
• Algorithm creation for transforming sensor data into actionable insights such as 3D model reconstruction, spatial data segmentation, and environmental feature detection

• Designing and developing new machine learning models with a focus on real-time performance
• Integrating cutting-edge ML features into the SkeleTRACK product
• Analysing model performance and identifying areas of improvement
• Mentoring junior engineers and driving technical discussions

• Building and evolving CI infrastructure validating performance methodologies across cloud, on-prem, and hardware targets
• Designing controlled, reproducible test environments to distinguish real regressions from environmental noise

• Building and optimizing inference pipelines for large-scale model serving
• Working with frameworks like PyTorch, TensorRT, and vLLM for efficient model deployment
• Implementing and optimizing ML models using quantization, kernel fusion, and efficient batching

• Leading and growing a cross-functional engineering team combining developers and QA engineers
• Collaborating closely with Product Managers and Designers to shape features from ideation to delivery focusing on usability, performance, and customer value

• Design and implement Data Pipelines in Snowflake
• Develop ingestion pipelines from various sources via Snowpipe and other means
• Create data transformations with SQL, Python, PaaS and 3rd party tools such as dbt
• Optimize existing pipelines and transformations for cost, load time, and maintainability

Development and enhancement of quantitative financial models Application of advanced technologies to real world financial problems Keeping up to date with the latest technological trends ...

• Setting technical direction across teams
• Driving AI-native and cloud-native architecture and long-term system evolution
• Leading design of secure, scalable MCP hosts and AWS microservices
• Balancing performance, reliability, and cost in system design

• Chunking and ingestion architecture with deterministic, validation-gated pipelines handling diverse enterprise document types with indexing and contextual enrichment
• Retrieval pipeline with vector search, BM25 hybrid retrieval, RRF re-ranking, embedding model selection and optimisation

• 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

• Magas szintű technikai és üzleti tanácsadás ügyfelek számára az Atlassian termékekkel és saját fejlesztésű megoldásokkal kapcsolatban
• Ügyfelek üzleti és IT folyamatainak felmérése, hatékonyságjavító komplex megoldások tervezése, bevezetése és minőségbiztosítása

• Architect and implement cloud-native data solutions using GCP (BigQuery, Dataflow, Pub/Sub, Dataproc, Cloud Composer, Cloud Storage)
• Lead the design and development of complex data pipelines and distributed processing frameworks that ensure scalability, performance, and operational reliability