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AI Genomic Sequencing Pipeline Engineer

Axion Labs

Remote · $160k – $200k / year · Full-time · Posted 3 months ago

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About the role

Our mission is to make precision medicine accessible beyond major research hospitals. Axion Labs builds AI systems that shorten the path from raw sequencing data to actionable genomic insight for smaller clinics and biotech partners. We already have a functioning variant-calling pipeline processing thousands of samples a month, but it wasn't built to scale past our current volume, and reprocessing older runs against new reference panels takes days instead of hours. You'll rebuild the batch processing layer, introduce checkpointed distributed jobs, and work with our wet-lab team to make sure pipeline changes never silently shift downstream clinical calls. This is a role for someone who reads papers on long-read sequencing for fun and wants to see that work reach real patients.

Responsibilities

  • Rewrite the batch variant-calling pipeline for distributed, checkpointed execution
  • Partner with the wet-lab team to validate that pipeline changes preserve clinical accuracy
  • Build reproducible reprocessing workflows for legacy sequencing runs
  • Own pipeline performance benchmarks and reduce reprocessing time from days to hours
  • Mentor two junior engineers working on adjacent bioinformatics tooling

Requirements

  • Production experience with distributed data processing (Spark or equivalent)
  • Hands-on background in genomics or bioinformatics pipelines
  • Comfort working directly with wet-lab scientists on validation
  • Experience with PyTorch for downstream modeling tasks
  • Familiarity with MLflow or similar experiment tracking tools

Benefits

  • Fully remote position
  • Equity in a Series B genomics company
  • Health, dental, and vision coverage
  • Annual conference and publication budget
  • Flexible PTO

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

Data Science & Analytics

Skills

python pytorch spark aws mlflow

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