Applied Research Scientist (Protein LMs) - Biotech
Job Description
Kadence is partnered with a bio x AI company in SF, looking for an Applied Research Scientist, for an on-site, full-time position.
The company is a Seed funded biotech operating at the intersection of molecular biology and machine learning.
What This Team Does:
This group sits between pure theory and production.
They:
- Understand the mathematical frameworks from the fundamental research team
- Implement them into high-performance code
- Optimize models for GPUs
- Scale pretraining
- Improve efficiency of inference and training
- Build the infrastructure for new architectures
They do not focus on biological interpretation, this is a strictly ML role.
Key Responsibilities:
- Implement new architectures from the theory team
- Optimize model code for high-performance training
- Handle model scaling, distributed training, and inference efficiency
- Work closely with the wet lab to ensure tight feedback loops
- Contribute to open-source foundation models and publications
Qualifications:
- Degree in CS, ML, Applied Math, or related
- Strong fundamentals in ML theory, optimization, and deep learning
- Experience building or training models from scratch (not just fine-tuning)
- Experience with PyTorch/JAX
- Strong high-performance computing background
- GitHub showing not mostly Python (C/C++/Julia/etc. is a plus)
- Research pedigree (top schools or top ML teams)
Who Thrives Here:
People who like writing elegant, hardware-aware code, scaling models, and working on fundamental research problems, but with implementation responsibility.