Location: San Francisco (US) or Berlin (GER)
Type: Permanent (Full-time)
Start Date: As soon as possible / by arrangement
ABOUT DAINA
DAiNA is a precision-oncology company focused on enabling personalized cancer treatment for individual patients. We combine comprehensive molecular tumor data including genomics, transcriptomics (bulk, single cell and spatial), proteomics and epigenetics, with AI-driven analysis. Our platform connects multi-omic profiling with functional ex-vivo tumor models and personalized liquid-biopsy monitoring, creating a continuous workflow from biopsy and treatment selection through to therapy monitoring and adaptation. We also operate GMP manufacturing to produce individualized N=1 therapeutics. In short, we help physicians make more informed, personalized treatment decisions based on high-dimensional molecular tumor data.
For more information, visit:
THE ROLE
As LLM Fine-tuning & Model Optimization Engineer, you will define how DAiNA adapts, evaluates and optimizes open-weight language models for biomedical and clinical use cases.
You will work on model selection, domain adaptation, fine-tuning, quantization, distillation and benchmarking. Your goal is to ensure that models are not only technically strong, but also reproducible, reliable and suitable for secure deployment in sensitive biomedical environments.
Your work will support DAiNA’s AI-driven reporting, biomedical knowledge retrieval, molecular interpretation and internal decision-support workflows. A key focus is to build repeatable and auditable methods for model adaptation while respecting data privacy, data residency and compliance requirements.
WHAT YOU’LL DO
WHAT YOU BRING
NICE TO HAVE
WHY DAINA
DAiNA is an equal-opportunity employer. We welcome applicants of every background and assess every candidate on merit, regardless of age, gender, ethnicity, religion, disability, sexual orientation or origin. If you need any adjustment to the process, let us know in your application.
#J-18808-LjbffrVeröffentlichungsdatum:
18 Aug 2026Standort:
BerlinTyp:
VollzeitArbeitsmodell:
Vor OrtKategorie:
Development & ITErfahrung:
2+ yearsArbeitsverhältnis:
Angestellt
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