Profluent Machine Learning Scientist at Profluent driving research into models at the intersection of protein biology and AI. Responsible for designing predictive and generative models using large-scale protein and nucleic acid data.
Responsibilities
Design and develop state-of-the-art predictive and generative models incorporating domain-specific evolutionary and experimental data
Leverage massive-scale protein and nucleic acid data to train specialized models for protein understanding and design
Curate relevant datasets and design tasks for rigorous evaluation of generative models
Collaborate across the machine learning and protein design teams to adapt and apply techniques for experimental validation
Implement, analyze, and interpret multiple computational approaches and present results to colleagues in regular update meetings
Work within a collaborative, fast-paced, interdisciplinary team across biology and machine learning to help shape the scientific and strategic vision of the company
Qualification
Experience with conceiving of3 to 5 years of industry experience
Required
PhD (or equivalent industry experience) in Computer Science, Machine Learning, Natural Language Processing, Applied Math, Computational Biology, Statistics, or a related field
Experience with conceiving of, implementing, and evaluating novel machine learning techniques at the intersection with biology
Publications at major machine learning conferences (NeurIPS, ICML, ICLR) or scientific journals (Nature, Science, Nature Biotech, Nature Methods, PNAS)
Experience with modern deep learning frameworks such as Pytorch or Jax
Familiarity with foundational biology of proteins and nucleic acids
