Job Details

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.