Machine Learning Expert (Bioinformatics)

This role is for machine learning specialists with a strong bioinformatics background who want short, well-paid projects applying models to real biological data. It suits published researchers who work well on their own and want hands-on experience with applied biotech problems at an early-stage, Y Combinator-backed startup.

What you'll do

• Build, train and assess models for tasks such as calling variants, analyzing gene expression or modeling pathways
• Work with genomic, transcriptomic, proteomic and multi-omics datasets using both supervised and unsupervised methods
• Design scalable, reproducible analysis pipelines that combine standard bioinformatics tooling with ML steps
• Keep clear written records of your methods, assumptions and technical choices

What you'll need

• A graduate degree (Master's or PhD) in a quantitative field such as bioinformatics, computational biology, computer science or data science
• At least one paper published as first author in a peer-reviewed journal
• Proven depth in both ML and biological data work, for example sequence analysis or genomics
• Nice to have: GATK, STAR, DESeq2, Nextflow or Snakemake experience, familiarity with scVI, DNABERT or Enformer, or time spent as a teaching assistant in related courses

Good to know

• Remote, asynchronous contract work paid at $150–$200 per hour
• Projects run over roughly two to three weeks, with 10–20 hours a week expected on the ones you take on