Python állás, munka

• 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

• Designing, implementing, testing, and optimizing reliable, efficient, and high-quality data pipelines
• Automating the extraction, loading and transformation of data from a wide variety of sources
• Developing solutions for the automated acquisition of data from source systems

• 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 optimization of data pipelines
• Writing clean, efficient and maintainable SQL and Python code

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

• Develop and maintain scalable web applications using Angular or React
• Build and optimize RESTful APIs and microservices using Node.js, Python or .NET
• Define and manage cloud infrastructure using Infrastructure as Code, such as Terraform or OpenTofu

• Új technológiák bevezetése
• Termékfejlesztési igények implementálása
• Rendszertervezés
• Tesztelés
• Dokumentálás
• Kapcsolódó alkalmazás- és interfészfejlesztésekben való együttműködés a társszervezőkkel
• Minőségbiztosítási feladatok támogatása

• Design and implement modern data architectures and lakehouse solutions
• Provide technical leadership throughout the project lifecycle
• Collaborate with business stakeholders
• Create effort estimations
• Provide technical expertise during the pre-sales phase
• Mentor 3-6 person project teams

• Lead the end-to-end implementation of data pipelines and GenAI applications on Databricks
• Design and maintain CI/CD, model serving, monitoring, and evaluation frameworks for AI production reliability
• Tune complex Spark jobs and LLM inference patterns for maximum efficiency and minimum latency

• Design and develop automation frameworks across frontend, backend, desktop, API, and data-driven systems
• Establish testing patterns and best practices for long-term maintainability
• Develop and maintain automated UI and end-to-end test suites using Playwright or Cypress

• Odoo-modulok fejlesztése és testreszabása Python 3, XML és HTML használatával
• Backend-szolgáltatások fejlesztése Java/Spring és Hibernate segítségével
• Külső rendszerek összekapcsolása REST- és XML-RPC-API-k segítségével
• Eseményalapú integráció az Apache Kafka segítségével

• Leading complex penetration testing engagements
• Working with enterprise-scale cloud and Kubernetes environments
• Mentoring other security professionals
• Helping clients understand and reduce real-world cyber risks

• Építés agentic rendszerek LangGraph / LangChain / PydanticAI / CrewAI használatával
• Integráció eszközök és adatok biztonságos kezelése időkorlátokkal, újrapróbálkozásokkal, idempotenciával és sebességkorlátozással

• Active partnership with sales and project managers to estimate, design, develop and deliver solutions
• Continuous communication with domain experts and product owners to understand core business needs and goals to synthesize requirement and quality standards

• Line management, coaching, and career development for a team of Full-Stack Engineers
• Performance management and professional growth fostering
• Fostering a culture of technical excellence

• Definition and development of system-level tests for high-end embedded computing systems
• Automation of test execution and evaluation through scripting in a CI environment
• Increase of test coverage by extending functional examples into comprehensive test suites

• Responsibility for the software architecture including fundamental software engineering non-functional and functional requirements and constraints
• Analysis of business and technical requirements for software platforms and infrastructure

• 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

• Design, develop, and implement complex, scalable Lakehouse solutions on the Databricks platform across major cloud environments
• Design, build, and optimize modular data pipelines using Delta Lake to ensure data efficiency, reliability, and quality