About Ten Lives
Ten Lives (YC S22) is pioneering research in AI and biology to feed the world, sustainably. Our flagship brand decarbonizes the pet food industry by reducing the fifth of the world’s meat consumed by pets.
About the role
Ten Lives is tackling the climate emergency by optimizing microbial factories with AI. With backing from YC / Collab Fund and NSF grants, we’re decoding the microbial genome to produce food proteins at the lowest cost and environmental impact.
Ten Lives is seeking a motivated Machine Learning Scientist to tackle the problem of DNA sequence design. This position offers an opportunity to work at the forefront of AI research, applying advances from natural language processing to the language of life - DNA. As an early employee, you will have the opportunity to lead research initiatives and collaborate with our interdisciplinary team of computational and experimental scientists.
What we offer at Ten Lives
- Real impact. Ten Lives can directly reduce global emissions by 1% by 2040.
- Supportive environment to explore, innovate, and drive research direction.
- We encourage publishing and presenting scientific findings.
- Competitive salary, comprehensive health insurance, PTO, and 401(k) matching.
- Hybrid / remote-friendly.
Responsibilities:
- Implement, optimize, and deploy state-of-the-art machine learning models for DNA sequence design.
- Develop efficient, robust code and data pipelines, ensuring high-quality results.
- Analyze and interpret computational approaches, presenting findings to colleagues in regular update meetings.
- Establish automated processes to continually evaluate and enhance our design methodology.
- Collaborate with diverse teams across biology and machine learning, contributing to the scientific and strategic vision of the company.
Qualifications:
- PhD degree in Machine Learning, Mathematics, Computational Biology, Statistics, Physics, or related disciplines.
- Demonstrated ability to implement and analyze state-of-the-art models for sequential data (text / genomic / time series) and/or expertise in explainability methods.
- Proficiency in writing clean and efficient code and deploying services on cloud computing platforms like GCP, AWS, or Azure.
- Interest in climate solutions and likes cats.
