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 dataBuild and scale distributed training pipelines (multi-GPU / multi-node)Optimize large-model training (FSDP, DeepSpeed, mixed precision, etc.)Deploy models into production research platformsImprove inference performance (quantization, distillation, optimization)Collaborate with computational biologists and platform engineers
Key experience needed:
4+ years of hands-on deep learning experienceStrong expertise with transformers and large-scale model trainingProduction experience deploying ML systemsAdvanced 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.
