AI RESEARCH SCIENTIST II/III

Unclassified - Boston, MA

Full-time - Mid Level

Boston, MA

About the position

1910 Genetics is a pioneering biotechnology startup that has developed a unique dual-purpose platform for small and large molecule drug discovery. This platform integrates artificial intelligence (AI), computation, and biological automation to create drug-like molecules more efficiently than traditional methods. Located in the Seaport District of Boston, the company was founded in 2018 and has garnered support from notable investors, including M12-Microsoft's Venture Fund and Sam Altman, CEO of OpenAI. The company focuses on understanding the molecular basis of diseases, akin to the detailed understanding of sickle cell anemia, and emphasizes that biology is the guiding principle in their approach to drug discovery. The integration of AI and computational technologies is crucial, but it is the experimental biology that drives impactful results in drug discovery. At 1910 Genetics, the role of an Individual Contributor (IC) is vital. The successful candidate will be expected to engage actively in drug design campaigns, leveraging the company's advanced AI/ML models. This position requires a proactive approach to staying informed about relevant scientific literature, prototyping innovative methods, and contributing to the ongoing drug design efforts. The company values a strong foundation in statistics and classical machine learning methods, as well as experience in deploying cutting-edge deep learning techniques. The ability to write clean, maintainable Python code and familiarity with MLOps and DevOps practices are essential for success in this role. Additionally, the candidate should have exposure to distributed computing environments such as Azure or AWS, and possess excellent communication skills to effectively share insights and findings with colleagues.

Responsibilities

• Proposing and prototyping AI/ML solutions that address use cases in our design pipeline.
• Applying productionized AI/ML models to advance our active drug design campaigns.
• Keeping up-to-date on cutting edge research in the AI for drug discovery space.
• Writing and publishing peer-reviewed scientific articles.
• Periodically presenting recent AI research at internal journal clubs.

Requirements

• 2+ years of relevant industry experience (AI, Drug Discovery, etc.).
• A first principles understanding of statistics and classical machine learning methods (SVM, RF, etc.).
• Industry experience training and deploying cutting edge deep learning methods (Transformers, Graph Neural Networks, etc.).
• The ability to write clean, maintainable, production-quality Python code.
• Familiarity with MLOps and DevOps best practices.
• Exposure to distributed computing (Azure, AWS, University Cluster, etc.).
• Excellent written and spoken communication skills.