kadence
ML Applied Scientist
My client is a biotech company using synthetic biology and AI to engineer microbes that convert carbon dioxide into valuable chemicals and materials. Their work focuses on creating sustainable, carbon-negative solutions for industries like fuels, polymers, and specialty chemicals.
About the job Responsibilities Work on in-house protein language models — design, build, test You will be implementing your own ideas Work with the lab team to produce the best proteins possible You will be expected to be deep in the THEORY and Implementation Not looking to hire any “ML engineers” or “Idea people” Work with the team on all of the above and more!
Qualifications PhD/Masters required in Computer Science/Statistics/Machine Learning/Math. Publication(s) in Math and/or THEORETICAL Machine Learning Preferred venues: NeurIPS, ICML, ICLR, AISTATS, UAI, JMLR/TMLR, IEEE TIT/PAMI, Annals of Math/Stats Has led/initiated their own research processes and is comfortable in a fast-paced environment. Must know how to code well Strong math background. My client is an early-stage startup, and things will break. They are looking for someone who is willing to roll up their sleeves and fix things.
Benefits Competitive base pay + equity options (0.5-1.5%). Full health and dental covered Based in SF, can cover relocation costs
My client is a biotech company using synthetic biology and AI to engineer microbes that convert carbon dioxide into valuable chemicals and materials. Their work focuses on creating sustainable, carbon-negative solutions for industries like fuels, polymers, and specialty chemicals.
About the job Responsibilities Work on in-house protein language models — design, build, test You will be implementing your own ideas Work with the lab team to produce the best proteins possible You will be expected to be deep in the THEORY and Implementation Not looking to hire any “ML engineers” or “Idea people” Work with the team on all of the above and more!
Qualifications PhD/Masters required in Computer Science/Statistics/Machine Learning/Math. Publication(s) in Math and/or THEORETICAL Machine Learning Preferred venues: NeurIPS, ICML, ICLR, AISTATS, UAI, JMLR/TMLR, IEEE TIT/PAMI, Annals of Math/Stats Has led/initiated their own research processes and is comfortable in a fast-paced environment. Must know how to code well Strong math background. My client is an early-stage startup, and things will break. They are looking for someone who is willing to roll up their sleeves and fix things.
Benefits Competitive base pay + equity options (0.5-1.5%). Full health and dental covered Based in SF, can cover relocation costs