Staff AI/ML Research Scientist

AI / ML Research Scientist | AI for Scientific Discovery (AI x Bio)Competitive Base + Meaningful EquityHybrid (San Francisco)AI-First Scientific R&D CompanyPLEASE FOLLOW THE KENKOTECH PAGE AND CONNECT WITH THE JOB POSTERWe're working with a well-capitalized, AI-native company building foundation models and learning systems to accelerate breakthroughs across biology and the life sciences.This team isn't just applying AI to science - they are rethinking how science itself is done. From training models that can reason over biological systems to developing autonomous workflows that generate and test hypotheses, their work sits at the frontier of AI x Bio.They are hiring AI / ML Research Scientists to push the boundaries of what machine learning can do in real-world scientific discovery. This is a deeply technical, research-driven role with direct impact on how new therapies, insights, and technologies are created.What You Will Work OnDevelop novel machine learning approaches for modeling complex biological systemsTrain and adapt large-scale models (e.g. foundation models, multimodal systems) on scientific dataDesign systems that can reason, generalize, and generate testable scientific hypothesesWork closely with engineers and domain experts to bring research into real-world workflowsExplore emerging paradigms (e.g. agentic systems, self-improving models, automated science)What They're Looking ForStrong background in machine learning / AI (PhD or equivalent industry experience)Experience developing and training deep learning models from first principlesHands-on experience with modern architectures (transformers, diffusion, multimodal models, etc.)Strong coding ability (Python, PyTorch and/or JAX)Bonus SkillsExperience with biological data (genomics, proteomics, drug discovery, etc.)Experience with large-scale model training or distributed systemsExperience with LLMs, reasoning systems, or agentic workflowsBackground in reinforcement learning or generative modelingTrack record of research (papers, open-source, or impactful industry work)Location & Work EnvironmentThis is a hybrid role. While remote candidates in the Eastern Time Zone (U.S.) are welcome, there is a preference for individuals able to periodically collaborate in person with the team.Interested candidates should apply via direct message or LinkedIn application.