Machine Learning Scientist; Bio x AI

Kadence Talent is partnered with a Seed funded Biotech company building protein foundation models for the biopharma industry.

We’re looking for a research scientist who thrives at the intersection of experimental biology and data-driven discovery. This role is ideal for someone who thinks in systems, designs experiments for learning (not just answers), and is excited to work in a fast-moving, platform-oriented environment.

You’ll collaborate closely with experimental and computational teammates to design, run, and interpret high-dimensional biological experiments that accelerate discovery.

• Design and execute experiments with learning and iteration in mind
• Partner with data and modeling teams to generate high-quality, model-ready datasets
• Own experimental design decisions, from assay structure to readout strategy
• Interpret complex, noisy biological data and translate it into actionable insight
• Contribute to building scalable discovery workflows, not one-off studies

• PhD or MS in biology, bioengineering, or a related quantitative life science
• Experience working with complex or high-dimensional biological data (e.g. phenotypic assays, functional genomics, single-cell, multi-omics)
• Strong intuition for experimental design, controls, and data quality
• Comfort working across wet-lab and computational contexts
• Ability to operate independently in an early-stage, fast-changing environment

• Experience designing assays intended for downstream modeling or reuse
• Familiarity with basic data analysis (Python/R) or close collaboration with ML teams
• Background in platform teams, early discovery, or multi-modality research

• High ownership and influence on how discovery is done
• Close collaboration across biology, data, and modeling
• Competitive compensation and meaningful equity
• Opportunity to help define a new standard for AI-enabled discovery

This role is 5 days per week from San Francisco.