Until is hiring: Machine Learning Engineer / Scientist in San Francisco
Until, San Francisco, CA, United States
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.
About You
Degree in Computer Science or a related field (Applied Mathematics, Statistics, Data Science, Computational Biology).
Excellent foundations in the mathematics that underlies machine learning, including linear algebra, probability, statistics, and calculus.
Strong experience in modern machine learning approaches, such as representation learning, generative modeling, active learning, and bayesian optimization.
Track record of developing ML approaches for scientific discovery, as evidenced by a strong publication record, substantial open source contributions, or deployment of a machine learning system in an industry role.
Demonstrated ability to write modular, maintainable, and performant code in Python.
Fluency with the Python data science and ML stack, including PyTorch, NumPy, SciPy, Pandas/Polars, Matplotlib/Plotly.
Proficient with developer tooling, including Linux command line, Git, and shell scripting.
Ability to think from first principles and tackle complex, cross-disciplinary problems with other scientists and engineers.
Preferred Qualifications
3+ years of relevant professional or research experience, or a PhD in a computational field.
Strong understanding of computer science fundamentals, including algorithms, operating systems, and concurrency.
Experience with cloud infrastructure (AWS, GCP) and SQL databases.
Benefits
Opportunity for outsized impact creating the future as an early team member.
Generous medical, dental and vision insurance coverage.
Flexible time off and paid holidays.
Competitive compensation package, including salary and equity.
401(k) retirement savings plan.
FSA and commuter benefits.
Subsidized lunch daily.
$140,000 - $240,000 a year
While this represents our expected range based on market data, final compensation will be determined based on your specific qualifications and may be outside this range. Please keep in mind that the equity portion of the offer is not included in this estimate.
As an equal opportunity employer, Until is committed to providing employment opportunities to all individuals. All applicants for positions at Until will be treated without regard to race, color, ethnicity, religion, sex, gender, gender identity and expression, sexual orientation, national origin, disability, age, marital status, veteran status, pregnancy, or any other basis prohibited by applicable law.
#J-18808-Ljbffr
In Summary: 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 . We envision a future where no transplantable organ is lost to logistics .
En Español: Hasta que una compañía moonshot construya un botón pause para la biología. Nuestro enfoque a corto plazo es criopreservación reversible en escala de órganos: preservar los órganos donados a temperaturas inferiores al cero sin formación de hielo, luego calentarlos uniformemente para el trasplante. Resolviendo este gran desafío, estamos sentando las bases para la crioprecesión reversible del cuerpo entero, dándole a los pacientes un puente hacia futuras curas. Para lograr nuestro objetivo, estamos reuniendo un equipo interdisciplinario para desarrollar sistemas de perfusión, formulaciones crioprotectoras, y hardware de vitrificación y recalentamiento. También estamos construyendo nuestro equipo de hibernación médica para abordar los retos de conservación total, comenzando con modelos roedores. Imaginamos un futuro donde no se pierda ningún órgano planeable, y ninguna información segura puede llegar pronto porque el descubrimiento final del diagnóstico de enfermedades biológicas será posible hasta que el próximo miembro del equipo científico de ingeniería logística sea capaz de comprender e impulsar una nueva tecnología científica de diseño. Tendrá proyectos de extremo a extremo que incluyen dar forma a la recopilación de datos y diseñar tuberías de datos, capacitar y evaluar modelos de aprendizaje automático, así como implementar herramientas que los científicos utilizan diariamente. Tiene un título en Informática o un campo relacionado (Matemáticas Aplicadas, Estadística, Ciencia de Datos, Biología Computacional). Excelentes bases en las matemáticas que subyacen al aprendizaje de máquinas, incluyendo álgebra lineal, probabilidad, estadísticas y cálculo. Una sólida experiencia en enfoques modernos de aprendizajes de máquina, tales como el aprendizaje representativo, modelado generativo, aprendizaje activo SQL, y optimización bayesiana. Seguir registro del desarrollo de métodos para descubrimiento científico, como lo demuestra una sólida publicación, contribuciones sustanciales de código abierto, o implementación de un sistema de aprendizado de máquina en una función industrial. Por favor, tenga en cuenta que la parte equitativa de la oferta no está incluida en esta estimación. Como empleador de igualdad de oportunidades, Until se compromete a proporcionar oportunidades de empleo para todas las personas. Todos los solicitantes de puestos en Until serán tratados sin importar raza, color, etnia, religión, sexo, género, identidad y expresión de género , orientación sexual, origen nacional, discapacidad, edad, estado civil, estatus veterano, embarazo o cualquier otro fundamento prohibido por la ley aplicable. #J-18808-Ljbffr
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.
About You
Degree in Computer Science or a related field (Applied Mathematics, Statistics, Data Science, Computational Biology).
Excellent foundations in the mathematics that underlies machine learning, including linear algebra, probability, statistics, and calculus.
Strong experience in modern machine learning approaches, such as representation learning, generative modeling, active learning, and bayesian optimization.
Track record of developing ML approaches for scientific discovery, as evidenced by a strong publication record, substantial open source contributions, or deployment of a machine learning system in an industry role.
Demonstrated ability to write modular, maintainable, and performant code in Python.
Fluency with the Python data science and ML stack, including PyTorch, NumPy, SciPy, Pandas/Polars, Matplotlib/Plotly.
Proficient with developer tooling, including Linux command line, Git, and shell scripting.
Ability to think from first principles and tackle complex, cross-disciplinary problems with other scientists and engineers.
Preferred Qualifications
3+ years of relevant professional or research experience, or a PhD in a computational field.
Strong understanding of computer science fundamentals, including algorithms, operating systems, and concurrency.
Experience with cloud infrastructure (AWS, GCP) and SQL databases.
Benefits
Opportunity for outsized impact creating the future as an early team member.
Generous medical, dental and vision insurance coverage.
Flexible time off and paid holidays.
Competitive compensation package, including salary and equity.
401(k) retirement savings plan.
FSA and commuter benefits.
Subsidized lunch daily.
$140,000 - $240,000 a year
While this represents our expected range based on market data, final compensation will be determined based on your specific qualifications and may be outside this range. Please keep in mind that the equity portion of the offer is not included in this estimate.
As an equal opportunity employer, Until is committed to providing employment opportunities to all individuals. All applicants for positions at Until will be treated without regard to race, color, ethnicity, religion, sex, gender, gender identity and expression, sexual orientation, national origin, disability, age, marital status, veteran status, pregnancy, or any other basis prohibited by applicable law.
#J-18808-Ljbffr
In Summary: 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 . We envision a future where no transplantable organ is lost to logistics .
En Español: Hasta que una compañía moonshot construya un botón pause para la biología. Nuestro enfoque a corto plazo es criopreservación reversible en escala de órganos: preservar los órganos donados a temperaturas inferiores al cero sin formación de hielo, luego calentarlos uniformemente para el trasplante. Resolviendo este gran desafío, estamos sentando las bases para la crioprecesión reversible del cuerpo entero, dándole a los pacientes un puente hacia futuras curas. Para lograr nuestro objetivo, estamos reuniendo un equipo interdisciplinario para desarrollar sistemas de perfusión, formulaciones crioprotectoras, y hardware de vitrificación y recalentamiento. También estamos construyendo nuestro equipo de hibernación médica para abordar los retos de conservación total, comenzando con modelos roedores. Imaginamos un futuro donde no se pierda ningún órgano planeable, y ninguna información segura puede llegar pronto porque el descubrimiento final del diagnóstico de enfermedades biológicas será posible hasta que el próximo miembro del equipo científico de ingeniería logística sea capaz de comprender e impulsar una nueva tecnología científica de diseño. Tendrá proyectos de extremo a extremo que incluyen dar forma a la recopilación de datos y diseñar tuberías de datos, capacitar y evaluar modelos de aprendizaje automático, así como implementar herramientas que los científicos utilizan diariamente. Tiene un título en Informática o un campo relacionado (Matemáticas Aplicadas, Estadística, Ciencia de Datos, Biología Computacional). Excelentes bases en las matemáticas que subyacen al aprendizaje de máquinas, incluyendo álgebra lineal, probabilidad, estadísticas y cálculo. Una sólida experiencia en enfoques modernos de aprendizajes de máquina, tales como el aprendizaje representativo, modelado generativo, aprendizaje activo SQL, y optimización bayesiana. Seguir registro del desarrollo de métodos para descubrimiento científico, como lo demuestra una sólida publicación, contribuciones sustanciales de código abierto, o implementación de un sistema de aprendizado de máquina en una función industrial. Por favor, tenga en cuenta que la parte equitativa de la oferta no está incluida en esta estimación. Como empleador de igualdad de oportunidades, Until se compromete a proporcionar oportunidades de empleo para todas las personas. Todos los solicitantes de puestos en Until serán tratados sin importar raza, color, etnia, religión, sexo, género, identidad y expresión de género , orientación sexual, origen nacional, discapacidad, edad, estado civil, estatus veterano, embarazo o cualquier otro fundamento prohibido por la ley aplicable. #J-18808-Ljbffr