Junior python developer állások Németországban (adatbázisszakértő)

• Architect and build the high-performance backbone of our data platform
• Focus on distributed computing stability and building effective caching strategies for large-scale operations
• Design ETL pipelines and architect resilient caching for complex dependency resolutions

- You own and continuously improve the Mixed-Signal ASIC design environment (EDA toolchain & flows) - You support analog and digital designers in complex CAD/EDA topics - You integrate and maintain PDKs, EDA tools and simulation environments - You troubleshoot design flow and tool issues across the...

• providing concepts, templates and implementations of AI service infrastructure and tooling
• taking an active part in bringing the developed AI-solutions to production in collaboration with the ML Engineers
• supporting review, monitoring and maintenance of the AI solutions

• Collaborate on quality inspection algorithms in challenging applications for factory environments
• Investigate potential of foundation models for industrial quality inspection
• Investigate XAI algorithms for Vision Language models

• Unique opportunity to contribute to the development of the SAP-RPT model family
• Design, develop and manage tools and data pipelines that enable the processing of tabular data at scale

• Design, develop, and operate reporting solutions for Procurement on our Data Lake - together with our team
• Take end-to-end responsibility for your reporting products: connecting data sources, developing and optimizing complex ETL pipelines, and modeling data according to a star schema

• Build Fullstack Features: Implement user-facing features using modern frameworks and connect them to backend APIs.
• Backend Development: Contribute to Python-based backend services (Django REST or FastAPI), including API endpoints and business logic.

Where you belong: Where you belong: ...

• You will contribute to improving our foundation recommender system
• Your role involves exploring and evaluating new machine learning methods, including applications of LLMs for recommender systems
• Expect to support personalized CRM communications (push notifications, in-app messages, newsletters)

Your role will be at the forefront of tackling complex challenges in the field of ophthalmology...

• Bring-up of new hardware in close cooperation with our electrical teams, providing robust interfaces for our high-level application teams
• Create drivers for new boards, components and sensors (e.g. optical & lightning)
• Evaluate new hardware based on EVK and development kits

• Develop and maintain ETL/ELT pipelines for both structured and unstructured data
• Ensure the integrity, availability, and performance of data across ingestion and storage layers
• Collaborate with analysts and architects to translate business requirements into scalable data models

You build and maintain end-to-end ML pipelines using workflow orchestration tools: from data ingestion to distributed training, evaluation, model compilation, and deployment-ready artefacts....

You design and build high-performance search and query pipelines over PB-scale MDF4 and MCAP data lakes, enabling ML engineers to find relevant driving scenarios, sensor conditions, and edge cases across billions of records in seconds....

• Prepare large-scale automated driving datasets for training and evaluation purposes.
• Contribute to the development and maintenance of the coding framework for data processing, model training, and validation of end-to-end driving systems.

• Architect and build the high-performance backbone of our data platform
• Focus on distributed computing stability and building effective caching strategies for large-scale operations
• Design ETL pipelines and architect resilient caching for complex dependency resolutions

• Develop methods and workflows to construct robust co-regulation networks from large single-cell and spatial transcriptomics datasets
• Integrate ontologies and metadata (e.g., tissue, cell type, developmental stage, treatment) to build tissue- and context-specific co-regulation networks

• Develop and optimize data pipelines and algorithms within the Snowflake environment.
• Manage code repositories, automate deployment processes, and collaborate with team members using Azure DevOps for continuous integration and machine learning model improvement.