Unlearn is advancing AI to eliminate trial and error in medicine by producing AI-generated digital twins of individual trial participants, enabling smaller and more efficient clinical trials to bring effective medicines to patients sooner.
Requirements
- 3-4+ years of experience developing machine learning models and adapting them to solve real-world problems.
- Previous experience with unsupervised ML, EBM, NLP, LLM, optimization theory, or reinforcement learning.
- Strong software engineering skills and collaborative software development.
- Fluency in the Python machine learning and data science ecosystem.
- Evidence of successful execution of ML projects in an industrial setting.
- Solid fundamentals in conceptual basics of ML architecture (linear algebra, statistics, optimization).
- Contributions to well-known open-source ML tools or frameworks.
Responsibilities
- Design and implement machine learning models to characterize and predict disease progression.
- Apply and fine-tune proprietary architectures to real-world clinical data.
- Clearly communicate technical findings and results to internal and external stakeholders.
- Stay up to date with developments in the ML field to inform Unlearn’s modeling work.
- Represent Unlearn to the broader scientific community.
Other
- M.S. in computer science or engineering, physics, mathematics, or a related field.
- Prior experience working with healthcare or clinical machine learning applications.
- Familiarity with AWS cloud computing services.
- Generous equity participation
- 100% company-covered medical, dental, & vision insurance plans
