Python programmer állás, munka

• Designing and delivering engineering solutions for our businesses and customers
• Enhancing our infrastructure capabilities and functions with new and fresh ideas
• Performing and improving QA and Test Automation frameworks

• Development and operation of the product in an engineering team
• Production deployments
• Cloud automation
• Monitoring and alerting
• Incident management and post-incident analysis
• Identification and troubleshooting of platform issues

• Designing and implementing novel human-computer interaction concepts
• Developing prototypes using modern hardware, sensors, and software tools
• Exploring eye-tracking-based interaction techniques and user interfaces
• Conducting user studies and evaluating interaction concepts

• Design and implement enterprise-scale data pipelines and advanced analytics dashboards
• Develop and optimize data ingestion, transformation, and modeling workflows across structured data environments and cloud-based platforms

Drive End-to-End Robotics Deployment: As a Chief Expert Robotics, you will lead the technical implementation and architecture of advanced robotic systems by translating complex algorithms into reliable, production-ready hardware and software solutions....

• Create and implement test strategies and concepts for all test levels in embedded, cloud, mobile and web applications
• Improve our development and testing processes, methods and tools, and support the development teams
• Plan, set up and maintain test environments and automation frameworks

Analyze AI computing systems end-to-end: Understand how training and inference workloads run on modern data-center architectures and identify the fundamental bottlenecks in compute, memory, interconnects and energy efficiency....

• Research and identify suitable prediction approaches, including kinematic and dynamic models, Kalman filters, regression techniques, data-driven methods, and hybrid approaches
• Implement prototypes in Python and integrate selected methods into C++ applications where appropriate

• An opportunity to build the foundation for next-generation products
• The option to write a master thesis following an internship or working student position
• Hands-on work on intrinsic, extrinsic, and multi-camera calibration for ZEISS use cases

• Lead design, development, implementation, validation, and continuous improvement of automation systems enhancing Inventory Control processes
• Drive automation projects from concept through deployment ensuring delivery on time, within scope, and aligned with business objectives

• Technical leadership and mentoring of data engineers
• Technical oversight for Databricks solutions
• Design and implementation of scalable ETL/ELT pipelines using Databricks, Python/PySpark, SQL, and Delta Lake

• An opportunity to build the foundation for next-generation products
• The possibility to learn and implement cutting edge 3D computer vision methods
• Mentorship by experienced PhD-level experts
• The option to write a master thesis following the internship

• Adatforrások integrálása a vállalat új Data Lakehouse platformján
• Adatbetöltési folyamatok fejlesztése a vállalat új Data Lakehouse platformján
• Skálázható adatfeldolgozó folyamatok fejlesztése
• Adattranszformációk fejlesztése
• Adatfeldolgozó folyamatok optimalizálása

• Building scalable testing frameworks
• Designing comprehensive test suites covering unit, integration, and acceptance testing
• Collaborating with engineers and data scientists to embed quality practices throughout the development lifecycle

• Analysis and research of cloud-native tools and frameworks for Google Cloud Platform solutions
• Support for the T-Systems Public Cloud Product Management Team in building and defining solutions

• Building one governed front door for every lead with validation, de-duplication, consent, and enrichment
• Building AI-native lead qualification models with comprehensive signal analysis and explainable scoring
• Building intelligent lead routing with territory, capacity, availability, and priority data

• Develop an efficient and reproducible workflow for application-oriented machine learning solutions.
• Be involved in sample preparation and data acquisition in the laboratory for full data ownership

• Fejlesztés és megvalósítás komplex generatív AI alkalmazásokban a felfedezéstől a bevezetésig
• Legjobb gyakorlatok keretrendszerének kialakítása felhőarchitektúrák telepítéséhez AI ügynökök támogatására, költség, teljesítmény és biztonság fókuszával LLM munkaterhelésekhez és vektor kereséshez

• Design, deploy, and manage scalable cloud and hybrid infrastructure environments with a primary focus on automation, reliability, and security
• Build and maintain Infrastructure-as-Code solutions using Terraform and other automation tools to provision and manage AWS and on-premises resources

• Data pipeline development
• Data integration
• Data warehousing
• Data modelling
• Data quality and governance
• Performance optimization
• Collaboration with data scientists and analysts
• Technology selection
• Security and compliance
• Monitoring and troubleshooting