Help us program biology.
Genomic Intelligence builds ultra-long context genomic foundation models to predict disease risk, explain heritability, and design actionable edits. It is a hard problem at the intersection of AI, biology, and systems — and a small team is going to solve it. We would like your help.
A few principles we actually hire and build against.
Slope over pedigree
We hire for trajectory and taste, not credentials. Show us something you built, proved, or figured out that others missed.
Close the loop
Prediction is only useful if it survives contact with a wet lab. We keep the distance between an in-silico hypothesis and a validated result short.
Work at genome scale
Megabase context, whole-genome pretraining, GPU serving under real load. The engineering and the science are the same problem here.
Small, interdisciplinary
AI, wet-lab biology, and systems engineering in one room. You will own real surface area and see your work reach the platform quickly.
We hire across the whole stack, from architecture to assay.
- AI research
Ultra-long context architectures, pretraining, and evaluation on genomic and multi-omics data.
- Computational biology
Variant effect, expression, and disease-risk modeling grounded in real biological signal.
- Wet-lab science
Assay design and validation that turns model predictions into experimental ground truth.
- Systems & infrastructure
Data platforms, distributed training, and low-latency GPU inference at production scale.
A sample of what we are hiring for right now.
- Apply
ML Research Engineer Long-context models
Design and train ultra-long context genomic foundation models; push architecture, data, and evaluation together.
- Apply
Genomics Scientist Wet-lab validation
Design assays that test model predictions and feed clean experimental signal back into training.
- Apply
Infrastructure Engineer GPU serving
Build the training and inference systems that keep megabase-scale models fast and reliable in production.
- Apply
Full-Stack Engineer Analysis platform
Turn genome-scale inference into interfaces researchers reach for daily, from API to product surface.
Roles are illustrative — we scope work around the person. If your strength sits between these, tell us where.
Don't see your role? Reach out anyway.
If genome-scale AI is the problem you want to spend the next years on, we want to hear from you — write to contact@genomicintelligence.ai and tell us what you would build.