Applied AI/ML Lead Engineer

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Applied AI / ML Lead Engineer
Location: Berlin, Germany
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: www.daina.com

THE ROLE
As Applied AI / ML Lead Engineer, you will help build DAiNA’s applied AI capability at the core
of our precision-oncology platform. Your focus will be on translating modern machine learning,
large language models and retrieval -augmented generation into robust, secure and clinically
relevant software systems.
You will design and implement AI-driven workflows that support molecular data interpretation,
clinical reporting, knowledge retrieval, decision support and digital -twin development. A key
part of the role is to ensure that sensitive patient and molecular data can be processed in a
secure, compliant and auditable environment, with strong control over model behavior, data
provenance and system performance.

WHAT YOU’LL DO
• Design, build and operate applied AI/ML systems for DAiNA’s precision-oncology platform
• Develop and maintain retrieval -augmented generation (RAG) architectures for molecular
data interpretation, clinical reporting, literature/knowledge retrieval and internal decision-
support workflows.
• Build robust components for document ingestion, chunking, embedding, vector search, re-
ranking, grounding, citation handling and evaluation.
• Deploy and operate open-weight and/or self-hosted models in secure cloud or isolated
environments, reducing unnecessary dependency on external AI providers for sensitive
patient data.
• Evaluate and fine-tune domain-specific models where this adds measurable value, using
reproducible training, validation and benchmarking workflows.
• Integrate AI components into DAiNA’s reporting layer, data platform and broader
computational oncology workflows.

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• Develop guardrails, audit trails, hallucination- control strategies and human-in -the-loop
review mechanisms for sensitive scientific and clinical use cases.
• Lead and coordinate a small distributed technical team or external specialists across
architecture, retrieval, model serving, fine-tuning and AI evaluation.
• Work closely with bioinformatics, data engineering, clinical, wet-lab and management
stakeholders to ensure AI systems address real workflow needs.

WHAT YOU BRING
• Strong software engineering background with hands -on experience building production-
grade ML, AI or LLM-based systems.
• Practical experience with large language models, including open-weight model families
• Deep practical understanding of RAG systems, including embeddings, vector databases,
chunking strategies, retrieval, re-ranking, grounding and evaluation.
• Experience with MLOps practices such as model/version management, automated
evaluation, monitoring, logging, deployment and reproducibility.
• Strong communication skills and the ability to explain technical trade-offs clearly to
scientific, clinical and management stakeholders.

NICE TO HAVE
• Experience in healthcare, biotech, diagnostics, pharma or another regulated environment.
• Experience with clinical or biomedical data, including molecular profiles, omics data,
pathology reports, clinical notes, literature, treatment guidelines or real-world evidence.
• Familiarity with digital twin approaches, computational oncology, cancer biology or
personalized medicine.

WHY DAINA?
• Employer contributions toward private health insurance or supplementary health coverage,
as well as pension or retirement savings.
• Hybrid model with ~60% of working time expected on-site and the rest remotely,
depending on team and business needs.
• Performance-based bonus opportunity, depending on company and individual performance.
• A personal development budget for conferences, courses, certifications, and training.
• The opportunity to work directly on real patient cases and help shape a first-in -class
precision-oncology platform
• A proactive, collaborative team with fast decision-making and strong ownership of your
domain.

HOW TO APPLY
Send your CV and a short note on why this role fits you to recruiting@daina.com , quoting
“Applied AI / ML Lead Engineer” in the subject line. We review applications on a rolling basis
and aim to reply quickly.

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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 t o
the process, let us know in your application.