Description:
We’re hiring a Lead Bio-ML Engineer to take ownership of our core machine learning systems.
This is a high-impact, high-autonomy role where you’ll:
- Own the end-to-end ML lifecycle (data, modelling, deployment)
- Work closely with biologists to translate experimental problems into ML solutions
- Build and scale models across areas like sequence modelling, structure prediction, and multimodal biological data
- Shape the technical direction and ML roadmap
- Mentor and grow a small team as they scale
What You’ll Do
- Designing models for genomics, proteomics, and drug discovery pipelines
- Applying deep learning / foundation models to biological datasets
- Building robust, production-ready ML systems (not just research prototypes)
- Developing internal tooling for data pipelines, experiment tracking, and model evaluation
What They Want
Core experience:
- Strong background in machine learning / AI engineering
- Experience applying ML to life sciences, bioinformatics, or computational biology
- Production experience with Python + PyTorch / TensorFlow
- Track record of owning and shipping ML systems end-to-end
Nice to have:
- Experience with biological data (e.g. sequencing, protein structures)
- Familiarity with drug discovery or wet-lab collaboration
- Exposure to LLMs / foundation models in biology
- Previous startup or high-ownership environment
Recap
- High ownership: you’ll define and build critical systems from the ground up
- Real-world impact: your work directly contributes to therapeutic discovery
- Tight feedback loop: collaborate daily with domain experts
- Equity upside: meaningful stake in an early-stage company
- Small, elite team: no bureaucracy, just execution