Description
Company Overview
We are the only AI-native biotech, pioneering small and large molecule therapeutics discovery by integrating massive multimodal data, frontier AI models, and high-throughput lab automation into an infrastructure for AI-enabled drug discovery.
We hire top 1% talent to join our interdisciplinary team of scientists, engineers, researchers, operators, innovators, drug developers, business professionals, and technologists.
Join us to build the world’s first AI infrastructure for tech-enabled drug discovery and to deliver a pipeline of diverse drug modalities for all major disease areas.
As an AI Research Scientist I at 1910 you will be expected to roll up your sleeves as an Individual Contributor (IC) by keeping up with relevant scientific literature, prototyping promising methods, and contributing to our active drug design campaigns by applying 1910’s productionized AI/ML models.
Role Description
Propose and prototype AI and Machine Learning solutions that address use cases in 1910’s design pipeline
Apply productized AI and Machine Learning models to advance 1910’s active drug design campaigns with the support of senior members of the AI Research Team
Write and publish peer reviewed scientific articles with the support of senior members of the AI Research Team
Periodically presenting recent AI research at internal journal clubs
Learn how a molecule processes through the drug discovery process
Work cross-functionally with scientific colleagues, being a subject matter expert in how AI and Machine Learning can be used to answer cheminformatics and bioinformatics questions
Keep up-to-date on cutting-edge research in the AI for drug discovery space
Qualifications
PhD in a relevant discipline (Computer Science, Biology, Chemistry, etc.)
A strong understanding of statistics and classical machine learning methods (SVM, RF, etc.)
Experience training and deploying cutting edge deep learning methods (Transformers, Graph Neural Networks, etc.)
Demonstrated experience writing clean, maintainable, production-quality Python code, with examples available in code repositories.
Familiarity with MLOps and DevOps best practices
Exposure to distributed computing (Microsoft Azure, HPC Cluster, etc.)
Ability to work effectively in a fast-paced startup environment with evolving projects and shifting priorities driven by business needs
Excellent written and verbal communication skills, including the ability to create clear documentation for roadmaps, proposals, and related materials
Nice to Haves
An understanding of how a molecule progresses through the drug discovery process
Relevant industry experience via internship and co-op (AI, Drug Discovery, etc.)
#LI-Onsite
Diversity and Inclusion (1910’s Promise)
At 1910, we believe that a diverse, equitable, and inclusive workplace furthers relevance, resilience, and longevity. We encourage people from all backgrounds, ages, abilities, and experiences to apply. 1910 is proud to be an equal-opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. If, due to a disability, you need an accommodation during any part of the interview process, please let your recruiter know. While 1910 supports visa sponsorship, sponsorship opportunities may be limited to certain roles and skills.
Benefits and Perks
- Competitive compensation package
- Above market benefits
- Generous vacation and parental leave
- Super cool team building activities
- Great colleagues
Company
1910.ai is an AI-native biotech company building the ITO Platform to accelerate drug discovery for small- and large-molecule therapeutics. The platform integrates multimodal data, frontier AI models, and high-throughput lab automation to provide an infrastructure for AI-enabled discovery. The company positions itself as a platform partner for pharmaceutical and biotech programs, offering collaboration through a Co-Engineering program to tailor data, models, and tools to client discovery goals. Public materials describe AI-driven advances, including PEGASUS models for macrocyclic peptides and CNS-target predictions, underscoring a product strategy that blends AI research with practical drug design workflows.
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