10 hours ago
Berlin, Germany +3 moreSenior
Responsibilities
- Own the design, development, testing, deployment, and security of data-rich tools, services, and web applications.
- Build scalable data ingestion, processing, cleaning, and orchestration pipelines for structured and unstructured data.
- Develop Python APIs and web applications or UIs for querying, exporting, analyzing, and visualizing data.
- Maintain data privacy, governance, and security standards across data architectures.
- Deploy and manage containerized data services using basic infrastructure tooling.
- Collaborate with materials scientists, machine learning engineers, partners, and other domain experts.
Requirements
- Have a software engineering background with a strong focus on data management.
- Demonstrate deep fluency in Python.
- Have hands-on experience with at least two database paradigms, such as relational, document, columnar, or key-value databases.
- Have a proven track record of building data-rich Python APIs and surfacing data through web applications with a UI.
- Have experience with complex unstructured data, large-scale datasets, and data privacy standards.
- Have experience with at least one modern orchestration framework, such as Dagster, Flyte, Prefect, or Ray.
- Have fundamental infrastructure experience with Docker and Kubernetes.
- Experience with geographically distributed data, data lakehouse or warehouse technologies, and collaboration with scientists, domain experts, or machine learning teams is beneficial.
Benefits
- Equity in CuspAI.
- 28 days of holiday in Germany, the Netherlands, and the UK, or 21 days in Japan, Singapore, and the US, in addition to local public holidays.
- Paid parental leave of 26 weeks for primary caregivers and 12 weeks for secondary caregivers.
- Professional development budget.
- Opportunity to work on AI-driven materials science, sustainability, and climate-related problems in an interdisciplinary team.
Tech Stack
Categories
BackendData Engineering
About CuspAI
CuspAI builds an AI-driven materials discovery platform that helps R&D teams in chemicals, energy, and manufacturing design and evaluate novel molecules and materials. The company offers software and models accessed via cloud APIs and collaborations to prioritize candidates, guide experiments, and shorten lab cycles. Founded in 2024 and headquartered in Cambridge, it is a privately held startup focused on applying generative and physics-informed AI to sustainability and next‑generation materials problems.