
51 - 200 employees
Founded 2015
🤖 Artificial Intelligence
🧬 Biotechnology
☁️ SaaS
Artificial Intelligence • Biotechnology • SaaS
TetraScience is a company dedicated to transforming raw scientific data into AI-native datasets for advanced scientific applications. By collaborating closely with leading biopharmaceutical companies, TetraScience enhances productivity, accelerates insights, and ensures data integrity across the scientific value chain. Their platform offers solutions for next-generation lab data management, AI-driven scientific outcomes, and compliance with industry standards. As the first company to provide a data and AI cloud built specifically for science, TetraScience enables its clients to liberate, unify, and transform their data, overcoming traditional data silos and boosting scientific productivity by providing a flexible, open, and collaborative infrastructure.
🕒 3 days ago
Principal Architect responsible for platform architecture and scaling for scientific data and AI in biopharma at TetraScience. Drive technical direction and oversee enterprise-grade capabilities in a rapidly growing environment.
🕒 July 6
Senior AI Platform Engineer at TetraScience to design and maintain cloud-native AI infrastructure. Collaborating cross-functionally to enable scalable AI/ML workflows and improve system performance.
🕒 July 1
Director of Scientific Solutions at TetraScience leading a team to implement scientific data solutions. Engaging with life sciences firms to transform scientific data into AI-ready assets and workflows.
🕒 June 24
Documentation Engineer at TetraScience building documentation systems and AI-augmented workflows for scientific AI platform. Leading documentation processes to enhance usability and clarity.
🕒 June 5
Lead Platform Engineer architecting and evolving a cloud-native platform for TetraScience. Focusing on high-throughput data processing and scalability in a remote-first environment.
🕒 May 11
Data & Semantic Model Architect at TetraScience creating a unified semantic framework for scientific data. Driving interoperability and collaboration across life sciences with advanced modeling strategies.