2 months ago
Base Salary
$136k - $167k/yr
Responsibilities
- Build datasets, tasks, and environments for evaluating and improving frontier AI models on complex scientific data.
- Analyze model failure modes and run experiments across frontier models to identify improvement opportunities.
- Build scalable data infrastructure and pipelines to curate, transform, and validate scientific data.
- Collaborate with frontier AI labs on approaches for improving models on challenging scientific tasks.
- Work with scientists to translate expert judgment into reliable problems and evaluation criteria.
Requirements
- Require 2+ years of experience at the intersection of biology and AI, including evaluating or improving scientific models or LLMs for biological applications.
- Require experience building with LLMs and understanding their strengths, limitations, and appropriate system designs.
- Seek curiosity about frontier AI and interest in advancing rapidly improving model capabilities.
- Require comfort working on ambiguous problems in a rapidly changing technical environment.
- Require collaborative work with engineers, scientists, and external research partners.
- Seek adaptability in a fast-paced environment where priorities can shift and rapid experimentation is encouraged.
Benefits
- In-office collaboration is prioritized, with work in the office Monday through Friday.
- Benchling is an equal opportunity employer committed to a diverse and inclusive workplace.
Categories
AI ResearchData Engineering
About Benchling
Benchling builds an R&D cloud and AI platform for life sciences, combining electronic lab notebooks, sample/registry management, workflow automation, and developer APIs to run models and integrate data. It sells subscriptions and services to biopharma, biotech, and research organizations; customers include Sanofi and Moderna. Founded in 2012 and headquartered in San Francisco, the company is privately held.