Python developer állás, munka

• Lead the technical lifecycle of ServiceNow and related governance platforms (IRM, Risk, Change, Incident, CMDB, Asset).
• Ensure configurations are secure, scalable, auditable, and aligned with regulatory standards.

Design, train, and evaluate machine learning models for manufacturing use cases such as quality prediction, anomaly detection, predictive maintenance, and process optimisation, covering the full ML lifecycle from problem definition to performance tuning....

• Own IAM strategy across Entra ID and Active Directory
• Manage conditional access, PIM/PAM, and identity lifecycle governance
• Develop identity-centric detections and threat-hunting workflows, analyzing Entra ID logs and privilege escalation paths in alignment with the SOC

• Build and maintain backend services and APIs using Java and Python
• Work on event-driven data pipelines based on Kafka
• Take ownership of services end-to-end: design, testing, deployment, monitoring, and iteration
• Ensure code quality, including writing and maintaining automated tests

Customer-Focused Outcomes: As a Senior SAP AI Engineer (f/m/d), you will be a key driver of customer value delivery, translating SAP AI architectural blueprints into fully functional, scalable, and production-ready solutions. Specifically, you will:...

You will analyse and evaluate technological developments and market trends in the areas of blockchain, DLT, smart contracts, tokenisation, CBDC and artificial intelligence....

• 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

• Build Data Pipelines: Design, build, and maintain scalable data pipelines for ingesting, transforming, and serving financial and operational data.
• Work with ERP Data: Integrate and model data from ERP systems and finance tools, including accounting, controlling, procurement, revenue, and cost data.

Analysis of the data ecosystem: assessment of data systems, interfaces and data quality; evaluation of security / privacy and interoperability (data-level to user-level)...

• Keep data moving: Build, run, and refine data pipelines and workflows (Python, Airflow/Cloud Composer) so they're reliable, fast, and easy to change
• Shape our data models: Use BigQueryand Cloud Spanner to design wellstructured, highperformance datasets for analytics and machinelearning use cases

• You understand RABOT's departments, their core processes and our AI tooling (Claude, Claude Code, our data stack) well enough to run a process-discovery session on your own.
• You've shipped your first automation into production — something a team feels immediately.

• 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)

• Design/build AI-ready Lakehouse architectures (Databricks, Fabric) and data pipelines for analytics/ML
• Develop financial data models (Data Vault 2.0) with governance (Purview, Unity Catalog)
• Architect AI infrastructure: Cognitive Search, RAG, vector DBs, knowledge graphs for agentic AI

As a Machine Learning Engineer in our Retail ML team, you will take end‑to‑end ownership of designing, developing and maintaining advanced machine learning solutions that directly influence our commercial performance. Your work will span dynamic pricing, demand forecasting and data‑driven buying...

• Design, maintain and deploy scalable, end-to-end training pipelines, including hyperparameter optimization
• Transfer control policies from simulation to real robotic hardware
• Integrate learned policies into a full-stack robotic system, including perception, planning, and actuation

• Work on design, coding, and quality assurance tasks related to specific product features.
• Build reliable, production-ready platform capabilities and help drive engineering quality across the team.
• Development activities in Java, Python, and Go, with Rust as a plus.

• Design and execute test cases for AI agent workflows (multi-steps reasoning, tool use, decision flows)
• Validate outputs of LLM-based systems for correctness and consistency
• Test end-to-end agentic pipelines
• Identify edge cases, hallucinations, and failure modes

Where you belong: Where you belong: ...

• Developing a transformer-based neural network for the processing of NMR spectra
• Creating datasets from existing experiments within the CRC and from your own experiments, which are to be carried out during a research stay at KIT's Institute of Microstructure Technology (IMT)

• 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)?