Machine Learning Scientist - Molecular Biology Interface

Kadence is partnered with a cutting-edge AI biotech startup building next-generation protein and biological sequence foundation models to accelerate drug discovery and protein engineering. They’re growing ahead of a planned Series A and are hiring a ML scientist who can bridge wet-lab biology and machine learning.

The Role

This position sits at the molecular biology & ML interface (not clinical/EHR). You’ll work closely with bench scientists and ML researchers to shape datasets, fine-tune sequence models, interpret outputs, and improve experimental/model feedback loops.

What You’ll Do

• Translate biological problems into ML-ready tasks
• Partner with wet-lab teams on dataset strategy, assay refinement, and data quality
• Fine-tune/evaluate protein and/or genomic language models
• Define biological success metrics and validation frameworks
• Support early co-discovery programs with industry partners

What We’re Looking For

Required:

• Background in molecular biology/bioengineering/genetics/biochemistry (or similar)
• Some wet-lab experience (bench work during training is fine)
• ML experience with biological sequences (protein/DNA/RNA, seq-to-function)
• Strong Python; comfortable analyzing model behavior and tradeoffs

Bonus:

• PhD and/or advanced research in ML-for-bio, comp bio, systems bio
• Protein modeling/generative sequence models
• PyTorch, JAX, HPC familiarity

Location:

5 days Onsite in San Francisco & Visa sponsorship available

Salary:

$150,000 - $200,000 base before equity and benefits