Research Scientist – Foundation Models and Multimodal AI
Core
Research Scientist adapting and fine-tuning open-weights foundation models for multimodal biological data (scRNA-seq, images, text) to build AI systems for pharmaceutical research.
Role type
Senior IC Research Scientist (Foundation Models & Multimodal AI)
Builds
Multimodal AI systems and production inference workflows for biological data analysis
Domain
Biotechnology / Pharmaceutical Research / Machine Learning
Deliverable
production ML models
Required skills
Fine-tuning foundation models, Cross-modal representation learning, Python, PyTorch, Hugging Face, Data engineering for multi-modal datasets
Preferred skills
Omics data experience (scRNA-seq, spatial transcriptomics), Cloud infrastructure (AWS/GCP), Containerization (Docker/Kubernetes), Open-source contributions
Technologies
PyTorch, Hugging Face, Parquet, AnnData, HDF5, Docker, Kubernetes, AWS, GCP
Responsibilities
Adapt and fine-tune open-source foundation models using transfer learning, Design cross-modal alignment architectures, Build benchmarking frameworks and evaluation pipelines, Integrate models into scalable production workflows, Identify incremental improvements in data pre-processing and embeddings
Seniority
Mid-Senior, hands-on IC
