The Senior Translational Scientist will translate mechanistic biological insights into target and biomarker hypotheses to improve patient outcome prediction. They will collaborate with AI researchers and computational biologists to integrate clinical and multi-omics data into foundation models for biomedical discovery.
You will own the AWS cloud foundation, infrastructure-as-code, and the development of self-service platforms to enable researchers and engineers. Additionally, you will manage CI/CD pipelines, security standards, and observability to ensure reliable and scalable infrastructure.
You will own the data and storage self-service layer, building infrastructure and tooling that allow researchers to access and process large multimodal biological datasets independently. You will also create internal services and paved roads to abstract complexity and ensure data security through code.
Join a talent pool for a fast-growing start-up building a universal AI foundation model for biology. Candidates will be considered for future roles across research, engineering, product, and business operations.
Join a talent pool to be considered for future internship opportunities in strategy, operations, finance, marketing, and business development. Support the growth of a universal AI foundation model for biology.
The role involves bridging the gap between unstructured real-world clinical data and AI models by designing data dictionaries and harmonizing data pipelines. You will act as the technical interface with global partners to ensure data quality and reproducibility using Python.
Lead the end-to-end development of B2B biology products, bridging the gap between AI research and reliable software. This includes designing scalable back-end services, APIs, and front-end interfaces while mentoring other engineers.
Own and scale the operational lifecycle of biomedical data partnerships, serving as the technical bridge between external partners and internal engineering teams. Manage secure data transfers, harmonization of multi-omics datasets, and the automation of ingestion pipelines.
The Clinical Expert will drive the clinical and scientific strategy for digital twin and data generation programs, focusing on onco-immunology. This includes prioritizing clinical questions, interpreting model outputs, and managing academic and pharmaceutical partnerships.
