The Company

Dyno Therapeutics is reshaping the gene therapy landscape through AI-powered vectors. Through the application of our transformative technologies and strategic partnerships with leaders in gene therapy, we believe a future with life changing gene therapies for millions of people is within reach. 

Our team includes world-class molecular and synthetic biologists, protein engineers and gene therapy scientists working alongside software engineers, data scientists, and machine learning experts to transform the landscape of available gene therapy capsids. Dyno was named Startup of the Year in 2020 by Xconomy, Endpoints 11 in 2021, and one of America’s Best Startups in 2022 by Forbes!

The Role

Machine Learning Scientist - Machine Learning Research. The Machine Learning Research team at Dyno is driving some of the world’s most cutting-edge work in ML-driven design of proteins. Your work as a part of this team will have a major impact on the future of gene therapy and protein design. In this role you will help solve the capsid design problem working together with people at the interface of ML, statistics, and biology. You are empowered to contribute to longer term research (and publications), as well as near-term impact. You will have access to an unmatched amount of real-world data, and your ideas can quickly be validated in experiments. You will work with and learn from computational and wet-lab experts in a highly collaborative environment. 

How You Will Contribute

As a Machine Learning Scientist you will be responsible for statistical data analyses, inventing machine learning models, advancing our computational optimization ability, and experimental design of libraries. There are ample opportunities in our platform to apply rigorous approaches from deep learning, optimization, reinforcement learning, natural language processing, and compressive sensing. The field of protein engineering is ripe with problems that are interesting and novel from an ML perspective, and Dyno is well-placed to generate data at a scale at which these approaches can be fruitful.

Who you are 

  • Team oriented
  • Thoughtful & detail oriented 
  • Passion for creative problem solving
  • Work with a sense of urgency
  • Appreciation for opportunities at the intersections of data science and biology

Basic qualifications

  • BS, MS, or Ph.D. in a quantitative field (Machine learning, Math, Physics, CS, Operations Research, Statistics, ...) or equivalent experience
  • Strong theoretical foundation in machine learning or a quantitative domain
  • Fluency with at least one machine learning library (such as Tensorflow or pyTorch)

Preferred qualifications

  • Proven track record of research in machine learning, including publications at major conferences (NeurIPS, ICLR, ICML) or scientific journals. 
  • Experience applying machine learning in a biological context. In particular, familiarity with recent advances in ML for protein engineering, including structure prediction models. 
  • One or more years experience working in a data science team in an AI company

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Job Type: Full-time

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