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Until is a moonshot company building a “pause button” for biology. Our near-term focus is organ-scale reversible cryopreservation: preserving donated organs at subzero temperatures without ice formation, then rewarming them uniformly for transplant. By solving this grand challenge, we’re laying the foundation for whole-body reversible cryopreservation, giving patients a bridge to future cures. To achieve our goal, we are assembling an interdisciplinary team to develop perfusion systems, cryoprotectant formulations, and vitrification and rewarming hardware. We are also building out our medical hibernation team to tackle the challenges of whole-body cryopreservation, beginning with rodent models. We envision a future where no transplantable organ is lost to logistics, and no terminal diagnosis is final because patients can safely wait for future medicine to arrive. About the Role As a Machine Learning Engineer / Scientist at Until, you will be an early member of the computational team defining how experimental data becomes insight and drives the next round of scientific discovery. You’ll build high-leverage ML systems that help develop new cryoprotectant formulations, engineer biologically-inspired antifreeze proteins, and understand the physics of vitrification and rewarming. You will own projects end-to-end including shaping data collection and designing data pipelines, training and evaluating models, and deploying tooling that scientists use daily.