Principal ML Scientist, Multimodal Biological Reasoning
Core
Lead the development of polyintelligent AI systems that unify human scientific expertise, machine intelligence, and biological signals into multi-modal reasoning engines for biology.
Role type
Principal ML Scientist (Strategy & Hands-on IC)
Builds
Multi-modal, multi-scale reasoning engines for biology integrated into an AI Scientist platform
Domain
AI-for-biology, computational biology, drug discovery, life sciences
Deliverable
production ML models
Required skills
modern LLMs, multimodal modeling, representation learning, fine-tuning, post-training, benchmarking, ML systems, computational biology, AI-for-biology, AI-enabled drug discovery, translational data science, biological foundation models, scientific discovery platforms, biological data modalities (genomics, transcriptomics, perturbation data, protein sequence, protein structure, pathways, imaging, pathology, time-series), mechanism-of-action reasoning, target discovery, perturbation biology, scientific credibility, model limitations, hallucination risk, interpretability, validation, leading small high-caliber technical teams, communicating with ML researchers and scientists
Preferred skills
experience deploying AI/ML for biology systems into scientific workflows at enterprise scale, experience with LLMs, biological foundation models, protein language models, genomic foundation models, scientific agents, AI discovery platforms, working across multiple internal and external customers, therapeutic programs, or discovery teams
Technologies
LLMs, biological foundation models, protein language models, genomic foundation models, scientific agents, AI discovery platforms
Responsibilities
Own the roadmap from architecture and data exploration through model readiness, benchmarking, refinement, and agentic integration; Guide technical architecture through a biological lens for multi-modal, multi-scale model design; Translate biology into model and evaluation requirements; Build the engine for a novel science platform by developing and integrating reasoning engines; Source and shape portfolio use cases by interfacing with teams and end-users; Communicate the impact by disseminating strategic direction and scientific results
Seniority
Principal, strategy & mentorship with hands-on technical leadership
