I’m currently partnering with a well-funded biotech company building large-scale AI models to accelerate drug discovery and biological research.
They’re hiring a Senior Deep Learning Engineer to focus on training, building, and deploying transformer-based models across biological data modalities.
Key responsibilities of the role:
- Design and implement transformer architectures for biological sequence and multimodal data
- Build and scale distributed training pipelines (multi-GPU / multi-node)
- Optimize large-model training (FSDP, DeepSpeed, mixed precision, etc.)
- Deploy models into production research platforms
- Improve inference performance (quantization, distillation, optimization)
- Collaborate with computational biologists and platform engineers
Key experience needed:
- 4+ years of hands-on deep learning experience
- Strong expertise with transformers and large-scale model training
- Production experience deploying ML systems
- Advanced proficiency in PyTorch (or similar framework)
- Experience working in high-performance compute environments
Biotech or biological sequence modeling experience is a strong plus, but strong transformer experience from other domains (LLMs, multimodal models, etc.) is also highly valued.
This is an opportunity to work on foundation-style models in biology with real-world scientific impact.
The role is pay a salary of up to $400,000 per annum and comes with a wealth of benefits. The role is hybrid 3 days a week in SF.
Apply within if this is interesting to you.