Machine learning software engineer állások, munkák Németországban

• Translate data into actionable insights that shape our marketing strategy and investments.
• Partner with marketing stakeholders to identify opportunities, define KPIs, and measure success.
• Build clear, engaging dashboards and reports that highlight trends and tell compelling stories.

Conduct field measurement campaigns using Rosenxt measurement technologies....

• Develop and maintain front-end interfaces with React (or Vue) for intuitive user experiences.
• Implement robust backend services and APIs using Node.js, TypeScript, and Python.
• Design, implement, and optimize database schemas across relational and non-relational systems.

• Implementation of software solutions for research purposes
• Translation of research code into robust software (e. g., optimization, refactoring)
• Contribution to research projects to allow deployment (containerization, virtualization)

• Contribute to the development of Gen/Agentic AI and Data solutions
• Get practical experience in implementation operation of AI Use cases across various business areas within Allianz Re
• Explore and ensure the quality of our comprehensive databases.

• Develop hardware-related software using CODESYS V3 and Siemens Step7
• Integrate modules into system architecture and contribute to platform development in C++
• Design and implement software following best practices (e.g., SOLID)
• Perform automated and manual testing to ensure quality

• Maintaining existing as well as creating new Linux applications on the unmanned aircraft.
• Designing and coordinating interfaces between teams, documenting the architecture and design decisions.

With us, you have the opportunity to perfectly combine your studies with practical experience while actively contributing to exciting projects. This allows you to gain valuable skills, expand your network, and grow both professionally and personally. We are seeking passionate and talented students...

implement and productionise ML-based services on our AI- and big-data-platform Databricks, using Python, SQL and Linux....

Develop a content-aware data compression method for Distributed Acoustic Sensing (DAS) data that dynamically adapts to the characteristics of the signal to maximize data reduction while preserving essential information required for downstream machine learning (ML) tasks....

Support enhancement of PD models, while ensuring compliance with different regulatory requirements (UK, EU) and internal standards....

• Assess processes to identify improvement and automation opportunities.
• Collaborate with stakeholders and cross-functional teams to define actionable solutions.
• Define the needs for application and data landscape to enable automation and AI integration.

• Leading engineering projects incl. team lead for vehicle power net testing & vehicle diagnostic
• Plan, execute, document, publish & present status & results to internal & external customers
• Use tools like CANalyzer, CANoe, and data loggers to collect and analyze system data

In this role, you will be doing a comprehensive assessment of diverse task categories, encompassing music, video, books, podcasts and home pod evaluations spanning various media domains...

• Design, configure, and optimize interactions with LLMs through retrieval-augmented generation (RAG), and orchestration.
• Implement tool-calling patterns to integrate LLMs with SaaS tools and APIs.
• Leverage fine-tuning or parameter-efficient techniques for performance enhancement.

• ongoing information on developments, discussions, and trends regarding the use of AI in research
• ongoing information on current and developing legal or compliance requirements
• ongoing development of the (AI) software portfolio provided to research and administration at the GIGA

• Use of new technologies in SAP's cloud services and products (e.g. machine learning, artificial intelligence)
• Implementation of new or amended data protection requirements based on applicable laws and regulations (e.g. international data transfers)
• Support of strategic data protection programs

• Partner with stakeholders to identify, design and evaluate AI solutions by translating complex business challenges into practical ML and GenAI use cases
• Lead data-driven projects, from requirements analysis to implementation, with a strong focus on business impact