Data engineer állások, munkák it programozás, fejlesztés területen

Explore and apply AI in real projects: Get hands-on with modern AI tools (e.g. Copilot, automation workflows, knowledge agents) and help us bring new digital solutions into everyday work...

You design and own end-to-end AI and data architectures - from data ingestion and feature pipelines to model deployment and monitoring - with a strong focus on production-grade edge AI inside the vehicle....

• Own the target picture, design, and continuous development of the global HR Data Architecture, embedded in the ZEISS Enterprise Vision
• Define how HR data is structured, integrated, and processed – with a focus on modular, integrated architectures, real-time analytics, and AI/ML readiness

• Design, develop, test, document, and deploy high quality Salesforce solutions leveraging Einstein 1 Platform, Lightning Web Components, and modern Apex patterns
• Analyze client specific requirements and define data model to support business, reporting and technical requirements

• Client-facing communication
• Participation in pre-sales discussions
• Collaboration with sales and customer success teams
• Communication with clients’ technical teams
• Solution design and configuration of data labeling and processing pipelines

• Developing and evaluating AI systems based on Large Language Models (LLMs), Vision-Language Models (VLMs), and multimodal foundation models
• Designing agentic workflows that automate complex image analysis tasks

• Monitor emerging AI developments across all domains and advise IT, leadership and internal stakeholders on opportunities arising from technological advancements in AI
• Identify and evaluate AI use cases together with administrative, scientific service and research units

• Define and execute the reporting and analytics transformation roadmap (towards lean target setup)
• Establish a scalable target architecture from data source through modelling and semantic layer to reporting frontend

• Design, develop, test, document, and deploy high quality Salesforce solutions leveraging Einstein 1 Platform, Lightning Web Components, and modern Apex patterns
• Analyze client specific requirements and define data model to support business, reporting, and technical requirements

Lead, Plan, and Deliver: You will own the technical execution for the AI team. This includes translating high-level user stories into clearly defined technical work packages, creating robust delivery plans in close cooperation with the SW Engineering Team and your own team, and ensuring timely,...

• Collaboration with senior product managers to ensure achievement of product objectives
• Support of key projects within the product management team
• Collaboration with research, engineering and program management teams

ARE YOU PREPARED FOR THE FUTURE? AI, AI SIR! Artificial Intelligence and machine learning are at the cutting edge when it comes to shaping next-gen mobility in areas like automated driving. But it takes real intellectual leadership and expertise to identify and then harness the AI trends and...

• Build and run evaluation pipelines for LLM-based systems
• Analyze metrics, identify edge cases, and track quality
• Create and maintain Golden and Silver datasets
• Work with evaluation frameworks and tools (like Langfuse)
• Develop Python scripts for AI workflows (APIs, data processing, monitoring)

• Investigate and resolve data inconsistencies across complex end-to-end data pipelines
• Automate complex analytics across large datasets to validate outputs and identify anomalies or inconsistencies
• Debug pipeline failures and improve overall pipeline robustness

• Implement and evaluate state-of-the-art motion planning and control approaches for highly unstructured environments
• Develop, refactor and maintain motion generation pipelines building blocks in a large robotics codebase
• Test approaches on real hardware in greenhouses

• Which structural and semantic gaps exist in the Celonis OCPM representation of the current Mercedes-Benz planning process?
• Which semantic concepts of our approach can be formalized as a Semantic Layer (e.g., as an ontology / knowledge graph)?

• Lead and manage international research programs across AI, Data Science, Simulation, Processes, and Quantum Computing.
• Build and run multi-partner research consortia with world-leading universities, tech networks, and public funding agencies.

You design and develop next-generation architecture at the intersection of multi-modal perception, foundation models, behavior learning, and end-to-end autonomous driving....

Where you belong: Where you belong: ...

• Definition and execution of the MDM transformation roadmap, transitioning from a complex carve-out environment to a streamlined PE-backed operating model
• Establishment of a scalable and pragmatic MDM framework aligned with business priorities