Machine Learning Engineer / Scientist

About Until

Until is an innovative company focused on creating a revolutionary "pause button" for biological processes. Their immediate objective is to master organ-scale reversible cryopreservation, which involves preserving donated organs at extremely low temperatures without ice forming, followed by uniform rewarming for transplantation. This breakthrough will pave the way for whole-body reversible cryopreservation, offering patients a means to await future medical cures safely.

The team integrates various disciplines to design perfusion systems, develop cryoprotectant compounds, and engineer vitrification and rewarming hardware. They are also expanding a medical hibernation unit to explore whole-body cryopreservation, starting with rodent experiments. Their vision is a world where no transplantable organ is lost due to timing or logistics, and terminal diagnoses can be deferred as patients await emerging treatments.

Role Overview

As a Machine Learning Engineer / Scientist, you will be among the foundational members of the computational group. You'll define methodologies to convert experimental data into actionable insights that fuel ongoing scientific breakthroughs. Your responsibilities include creating powerful machine learning frameworks to innovate cryoprotectant formulas, bioengineer antifreeze proteins, and analyze the physics behind vitrification and rewarming. You will independently manage projects from data acquisition strategies and pipeline creation to model development, validation, and deployment of tools used daily by scientists.

Candidate Profile

• Possess a degree in Computer Science, Applied Mathematics, Statistics, Data Science, Computational Biology, or a related discipline.
• Have strong foundational knowledge in mathematics essential to machine learning: linear algebra, probability, statistics, and calculus.
• Experience with contemporary machine learning techniques including representation learning, generative models, active learning, and Bayesian optimization.
• Proven track record applying ML in scientific discovery evidenced by publications, major open-source projects, or industry ML deployments.
• Proficient in writing modular, efficient, and maintainable Python code.
• Experienced working with Python data science and machine learning tools such as PyTorch, NumPy, SciPy, Pandas or Polars, and visualization libraries like Matplotlib or Plotly.
• Comfortable with developer tools such as Linux command line, Git version control, and shell scripting.
• Adept at first-principles thinking and collaborating on intricate interdisciplinary problems with researchers and engineers.

Preferred Qualifications

• Over three years of relevant professional or research experience, or a PhD in a computational field.
• Comprehensive understanding of computer science fundamentals encompassing algorithms, operating systems, and concurrency.
• Familiarity with cloud platforms (AWS, GCP) and SQL-based databases.

Benefits and Inclusion

• Chance to make significant contributions as an early team member shaping future technology.
• Extensive healthcare benefits including medical, dental, and vision insurance.
• Flexible vacation policies and paid holidays.
• Competitive remuneration packages comprising salary and equity.
• Participation in company 401(k) retirement plan.
• Access to flexible spending accounts and commuter benefits.
• Daily subsidized lunches.

Diversity Commitment

Until is an equal opportunity employer devoted to fair hiring practices regardless of race, ethnicity, religion, gender identity or expression, sexual orientation, national origin, disability, age, marital status, veteran status, pregnancy, or any legally protected category.

Hiring Process Data Privacy

Artificial intelligence tools may be leveraged for application sorting, resume analysis, and response evaluation, yet all final decisions are human made. Candidates can inquire about data handling procedures.