AI Scientist

IMMEDIATE HIREOverviewRead the full description before applying.MUST HAVE: In-depth understanding and experience with developing novel multimodal LLM architectures and Reinforcement Learning. Available to work full-time and on-site 3 days a week.At M31 Biomedical AI, we are redefining how artificial intelligence understands human health and biology. Our models power universal segmentation and imaging analysis across multiple medical modalities to uncover new biological and clinical insights.We’re seeking a full-time AI Scientist to support the development of multimodal biomedical foundation models incorporating SOTA LLM architectures, training frameworks (i.e. Reinforcement Learning, JEPA) and other methodologies. You’ll be working with a diverse team of AI researchers, clinicians, and computational biologists to explore how deep learning can advance personalized medicine and healthcare for patients.This position is ideal for someone passionate about biomedical AI, multi-modal data, and collaborative, high-impact research.What You’ll DoDefine research direction to incorporate SOTA multimodal LLM methodologies to foundational models for biomedical applicationsDefine data input, model outputs, labels and outcomes to develop clinically and biologically meaningful model objectives.Design experiments to critically assess model performanceContribute to publications in leading conferences and journals, and open source software that advance the field of biomedical AIBuild, review and maintain reproducible and modular codebases for training and running experiments with deep learning modelsCollaborate with research partners to collect, preprocess, and harmonize structured and unstructured clinical data, pathology and radiology images.Work closely with data scientists and clinicians to ensure scientific and clinical relevanceDiscover, validate and implement new AI tools to improve workflow efficiencyDocument and maintain reproducible workflows using Git, Python, and cloud-based toolsContribute to publications, internal reports, and presentations summarizing key findingsCreate clear, compelling presentations and visualizations that translate highly technical results for both clinical and technical audiencesWhy Join UsBe part of a leading biomedical imaging AI company recognized for its foundational work in universal segmentationCollaborate with top academic and hospital research teams on cutting-edge multi-modal AI projectsGain exposure to large, high-quality datasets spanning medical imaging and clinical dataWork in a mission-driven environment that bridges scientific research and real-world healthcare impactEnjoy flexible work arrangements, mentorship, and opportunities for authorship and recognitionRequired Skills & BackgroundMaster’s or PhD (or equivalent experience) in Engineering, Computer Science, Mathematics, Biomedical Engineering, Computational Biology or a related field.Strong theoretical understanding of transformers, SOTA LLM architectures and reinforcement learningExtensive experience developing multimodal LLM architecturesStrong programming experience in Python and ML frameworks (e.g., PyTorch, TensorFlow, MONAI)Background in analyzing biomedical or life science dataUnderstanding of at least one of the following domains:Clinical data (EHR, laboratory results, disease outcomes)Medical imaging (MRI, CT, pathology, etc.)Experience with data management, reproducibility, and collaborative code developmentExcellent problem-solving, communication, and teamwork skillsStrong publication record in leading academic journals and conferencesNice-to-HaveBiomedical domain knowledge (disease pathophysiology, human anatomy, cellular biology)Experience with agentic coding tools (Claude Code, Codex)Previous work involving multi-institutional datasetsApplication RequirementsResume/CVCover letter describing your experience and motivation for working on patient-centric clinical foundation modelsGitHub portfolio or publications (optional but encouraged)About M31M31 Biomedical AI is a biomedical imaging company developing foundation models for medical image segmentation and analysis. Our technology enables universal understanding of medical images across modalities and institutions.We’re now collaborating with leading research partners to extend this vision beyond imaging to include multi-modal clinical data, in order to advance patient healthcare, understand complex diseases and improve therapeutic discovery.Job Type: Full-time (12-month renewable contract)Location: Hybrid remote – Toronto, ON (M5S 1A8)Compensation: CA$85,000 - $100,000, based on experience

Benefits

Flexible scheduleWork-from-home optionMentorship and publication opportunities