Your tasks

• Develop production-ready software – APIs, services and internal web apps in modern Python (uv, FastAPI/uvicorn), with clean architecture, tests and CI/CD; for example, analysis apps that allow researchers to evaluate their test data, deployed as Databricks apps via Asset Bundles and GitLab.
• Develop AI applications for research – assistants and agents that support R&D in tasks such as research, hypothesis generation, material selection, and synthesis planning. You combine LLMs and agents (including Claude via MCP) with scientific methods such as cheminformatics, retrosynthesis, and quantum chemistry – and continuously advance these tools.
• Think AI broadly – ​​not just LLMs – use classic machine learning where it is the better tool: modeling relationships between material and performance, detecting data quality and anomalies, predicting lifespan and degradation.
• Building and operating scalable data pipelines and our data platform – according to the Bronze/Silver/Gold principle on Databricks and Azure, from sensor ingestion (MQTT, Event Hubs, Lakeflow) to the Gold tables that the business units work with directly.
• Take responsibility for your systems end-to-end – from the data source through the model or agent to the tool in the hands of the researchers, including security, observability, quality and reliability.
• Working closely with chemistry, electrochemistry, engineering and testing, and translating scientific questions into software and AI solutions.

Your profile

• You are primarily a strong developer – with several years of experience in building production-ready software, with a feel for architecture, clean code, testing and CI/CD (ideally GitLab).
• You have a very secure command of Python (and SQL) and are at home in the design of APIs, services and microservices.
• You have solid data engineering experience – Databricks and PySpark, the medallion architecture (Bronze/Silver/Gold), batch and streaming pipelines, and the Azure data stack (Data Factory, ADLS Gen2, Event Hubs).
• You have a genuine affinity for AI across the board – practical experience with LLMs and generative AI (RAG, agents, MCP, tools like Claude) and a solid understanding of classical machine learning – and you know when to use what.
• You want to work at the interface of software, data, AI and natural sciences and have the curiosity to delve into our domain – batteries, chemistry, electrochemistry.
• Excellent English skills; German is an advantage.

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Your tasks

• Develop production-ready software – APIs, services and internal web apps in modern Python (uv, FastAPI/uvicorn), with clean architecture, tests and CI/CD; for example, analysis apps that allow researchers to evaluate their test data, deployed as Databricks apps via Asset Bundles and GitLab.
• Develop AI applications for research – assistants and agents that support R&D in tasks such as research, hypothesis generation, material selection, and synthesis planning. You combine LLMs and agents (including Claude via MCP) with scientific methods such as cheminformatics, retrosynthesis, and quantum chemistry – and continuously advance these tools.
• Think AI broadly – ​​not just LLMs – use classic machine learning where it is the better tool: modeling relationships between material and performance, detecting data quality and anomalies, predicting lifespan and degradation.
• Building and operating scalable data pipelines and our data platform – according to the Bronze/Silver/Gold principle on Databricks and Azure, from sensor ingestion (MQTT, Event Hubs, Lakeflow) to the Gold tables that the business units work with directly.
• Take responsibility for your systems end-to-end – from the data source through the model or agent to the tool in the hands of the researchers, including security, observability, quality and reliability.
• Working closely with chemistry, electrochemistry, engineering and testing, and translating scientific questions into software and AI solutions.

Your profile

• You are primarily a strong developer – with several years of experience in building production-ready software, with a feel for architecture, clean code, testing and CI/CD (ideally GitLab).
• You have a very secure command of Python (and SQL) and are at home in the design of APIs, services and microservices.
• You have solid data engineering experience – Databricks and PySpark, the medallion architecture (Bronze/Silver/Gold), batch and streaming pipelines, and the Azure data stack (Data Factory, ADLS Gen2, Event Hubs).
• You have a genuine affinity for AI across the board – practical experience with LLMs and generative AI (RAG, agents, MCP, tools like Claude) and a solid understanding of classical machine learning – and you know when to use what.
• You want to work at the interface of software, data, AI and natural sciences and have the curiosity to delve into our domain – batteries, chemistry, electrochemistry.
• Excellent English skills; German is an advantage.