Recursion
Decoding Biology to Radically Improve Lives
About Recursion
Funding & Growth
✓ Pros
- • Innovative AI-first approach
- • Unique phenomics platform
- • Strong ML/AI culture
- • Remote-friendly
- • NVIDIA partnership
✗ Cons
- • Salt Lake City location
- • Stock volatility
- • Early drug pipeline
- • Lower base pay (equity heavy)
🏢 Working Here
Recursion Pharmaceuticals in Salt Lake City, UT, represents a radically different approach to drug discovery - industrial-scale phenotypic screening combined with AI.
The company has built one of the world's largest biological datasets, imaging billions of cells under different perturbations.
Computational biologists at Recursion analyze high-content imaging data, train deep learning models to predict drug effects, and integrate multi-modal data (imaging, transcriptomics, proteomics).
Teams include Computer Vision (extracting features from microscopy images), Machine Learning (predicting drug-disease matches), Cheminformatics (virtual screening), and Bioinformatics (analyzing transcriptomic and genomic data).
The culture is unique - combining biology, computer vision, and drug discovery.
Utah location offers exceptional quality of life, low cost of living, and access to outdoor recreation, attracting scientists who value work-life balance.
Recursion is public (NASDAQ: RXRX) and well-funded with partnerships with Roche, Bayer.
🧬 Bioinformatics Focus
Recursion's computational approach centers on using machine learning to accelerate drug discovery. Core areas:
- Computer vision for cell imaging - extracting morphological features from microscopy images using CNNs, developing embedding spaces that capture biological state,
- Drug - disease matching - predicting which compounds will reverse disease phenotypes based on learned representations,
- Multi - modal learning - integrating imaging, transcriptomics (L1000), and chemical structure data,
- GWAS to drug hypotheses - using genetics to guide screening efforts,
- Clinical biomarker discovery - identifying patient populations for pipeline compounds. Recursion's dataset is unprecedented: >4 petabytes of imaging data from >2 billion cells across thousands of genetic and chemical perturbations. The computational challenges include developing interpretable ML models (important for mechanistic understanding), handling class imbalance (rare disease phenotypes), scaling computer vision to petabyte datasets, and validating computational predictions experimentally. The team has published in Cell Systems, Nature Communications, and pioneered approaches in self-supervised learning for biology. Partnerships with Bayer (fibrosis) and Roche (neuroscience) validate the platform.
📈 Career Growth & Development
Career Paths
Computational Biologist/ML Engineer
Compensation
As a public company, Recursion provides equity compensation including RSUs, offering market liquidity.
Development
Professional development includes publishing papers, presenting at leading ML and drug discovery conferences, and contributing to open-source projects.
Mobility
Recursion alumni join other AI-in-drug-discovery companies, tech giants, or launch their own ventures, demonstrating highly transferable skills.
Culture
Recursion fosters a family-friendly culture in Utah, leading to low attrition and long employee tenures.
Growth
Recursion's growth, now with 300+ employees, creates advancement opportunities within the company.