Research Scientist, Life SciencesActive$300K

The opportunity

Build and ship agentic tools and integrations that let Claude execute real life science workflows — bioinformatics pipelines, database queries, analysis notebooks, literature review

What you'll do

  • Build and ship agentic tools and integrations that let Claude execute real: life science workflows — bioinformatics pipelines, database queries, analysis notebooks, literature review

  • Design and build evaluation benchmarks that measure model capabilities on: biology tasks — figure interpretation, bioinformatics, protocol reasoning, literature synthesis

  • Work closely with product and design teams to scope, prototype, and ship features for life sciences users

  • Partner with external biotech, pharma, and academic users to understand their: workflows and turn feedback into product improvements

  • Build and maintain the engineering infrastructure behind our biology product: surface — tool scaffolding, data pipelines, eval harnesses

  • Translate biological domain knowledge into product requirements and: evaluation criteria that guide model improvement

What they're looking for

  • + years of experience applying ML and software engineering to biological: problems — computational biology, bioinformatics, protein ML, genomics, or similar
  • Ph.D. in computational biology, bioinformatics, bioengineering, CS, or a: related quantitative field — or equivalent industry experience
  • Experience with LLM post-training: RLHF, RL from verifiable rewards, SFT data curation, or eval-driven development
  • Direct experience with therapeutic discovery pipelines: target identification, lead optimization, ADMET modeling, or clinical data analysis
  • Familiarity with bioinformatics tooling and pipelines (sequence analysis,: structure prediction, single-cell, variant calling, etc.)
  • Experience building agentic systems or tool-use environments
  • Published research in ML for biology, or open-source contributions to computational biology tools
  • Fluency with biological databases (UniProt, PDB, Ensembl, NCBI) and the: ability to reason about their schemas and failure modes