About Foresite Labs
Foresite Labs incubates companies that will address some of our greatest unmet medical needs. We believe that the tools of AI and data science, when applied with scientific rigor, will greatly accelerate scientific discovery and the development of new products and services that benefit patients. Our work powers drug discovery and company formation, and provides the core around which new ideas are realized and incubated. We offer competitive salaries, excellent benefits, a flexible work environment, and the opportunity to learn from top thinkers in various disciplines. Foresite Labs is headquartered in San Francisco and Boston.
Role
We are seeking an AI engineer with deep experience in building AI-driven applications and an interest in biotech to join our team. You would be joining to build a high-profile internal product that will transform how Labs operates. We offer a flexible work environment, a diverse set of projects, and a best-in-class peer group to learn from, including peers with experience at Google, Meta, and other top-tier tech and biotech companies. This is a great opportunity to tackle a unique set of problems while shaping the future of healthcare.
Responsibilities
- Build systems that integrate structured and unstructured information on biological and biotech-related problems using the latest methods in AI, including LLMs.
- End to end development of AI applications, including method and model selection, fine tuning, prompt engineering, performance assessment, and collaboration with engineering teams to integrate AI into broader systems.
- Work with domain experts and data engineers to organize and curate the datasets that power these applications.
- Develop an understanding of biology, biotech investing, and drug development in the course of building these applications.
Qualifications
- Masters, PhD, or equivalent in a computational or quantitative field (e.g., computer science, computational biology, bioinformatics, statistics, or mathematics).
- 3-10+ years of relevant work experience.
- Experience with the application of AI structured and unstructured datasets, including integration of LLMs (local and via APIs) into applications, vector databases, and integration of such tools with classical methods.
- Hands-on knowledge of modern AI frameworks, (e.g., PyTorch), including their integration into production workflows.
- Rigorous understanding of emerging and foundational machine learning methods, including deep learning (transformers, CNNs, etc.), tree-based methods, regularized regression and classification modeling, and dimensionality reduction (supervised and unsupervised).
- Industrial software engineering skills and discipline, including knowledge of at least one scripting language (e.g., Python) and database language (e.g., SQL), rigorous testing practices, and distributed tools for model training and fine tuning.
Salary Range: $174,282 - $218,426
Foresite Labs is an equal opportunity employer. We thrive on diversity and collaboration.
Please submit a complete CV, not an abbreviated résumé.
Top Skills
What We Do
Foresite Labs incubates companies that will address some of our greatest unmet medical needs. Their experienced team of scientists, engineers, and operators believes that the tools of data science, when applied with scientific rigor, will greatly accelerate scientific discovery and the development of new products and services that benefit patients. Through its incubation platform, Foresite Labs is dismantling the barriers faced by visionary entrepreneurs and their companies as they seek to re-invent healthcare.
Foresite Labs Values
Truth over progression: We follow the science, pursuing ideas that are grounded in data and abandoning them when not supported by the evidence.
Take good risks: Our culture values informed risk-taking: good decisions are celebrated even when they result in bad outcomes. Everyone feels safe to contribute ideas and to learn from failure.
Single accountable person: The project team lead is accountable for all decisions and for maintaining transparency and information flow within the team; we trust the project teams. The Review Committee unlocks capital and sets directions.
Simplicity and Focus: “Companies die from indigestion, not starvation” (Bill Hewlett) We will focus on a few ideas aggressively and minimize all other distractions. Everyone will have a few key goals that have measurable outcomes.
Respect and Community: Our employees are our greatest asset; everyone invests in creating an environment of collaboration and respect. We support their careers and career development whether they stay, go to a Labs company, or end up somewhere else.