Scientist I/II, Machine Learning/AI Protein Design

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Tessera is seeking a talented, creative, and enthusiastic scientist to join our expanding Data Sciences team. You will apply machine learning techniques and deep neural network models to support the discovery and engineering of novel gene editing technologies. This role will contribute scientific and technical expertise to a multidisciplinary team, emphasizing conceptualization, experimentation, data analysis, presentation, and strategic planning.

The Data Science group is part of a rapidly growing, multi-disciplinary “digital” department and will work closely with colleagues in Computational Biology, Protein & RNA Engineering, Data Engineering, Software Engineering, etc. as well as experimental scientists across Research, external collaborators, partners, and more.

Key Responsibilities:

• Develop and apply protein modeling and design strategies to advance Tessera's Gene Writing platform.
• Devise, train, refine, and deploy deep neural network models using public and proprietary sequence, structure, and function data.
• Collaborate closely with experimental scientists to close the model-test-learn loop.
• Drive external collaborations where necessary to augment internal capabilities.
• Leverage public datasets where possible.
• Present scientific findings to broad audiences including senior leadership to drive decision making in program teams.

Basic Qualifications:

• Ph.D. in Computational Biology, Computer Science, Mathematics, or related discipline.
• 3+ years of experience (including PhD work) in applying deep learning methods to problems related to protein sequence-structure-function relationships (e.g., protein structure prediction, protein annotation, novel sequence generation, function or property prediction, de novo design, directed evolution, etc.)
• Demonstrated ability to deliver deep learning models to production use.
• Strong technical proficiency in coding (including ML frameworks), cloud computing, and dev ops.
• Outstanding written and verbal communication skills, ability to work with colleagues from diverse scientific backgrounds and cultures.
• Preferably a track record of success working in a fast-paced, cross-functional, and rapidly growing biotech organization.
• Ideally experience with recent advances in gene therapy and development of gene editing platforms as therapeutics.