Bioinformatics Engineer, Pipelines

Mithrl · San Francisco · FullTime

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ABOUT MITHRL

We imagine a world where new medicines reach patients in months, not years, and where scientific breakthroughs happen at the speed of thought.

Mithrl is building the world’s first commercially available AI Co-Scientist. It is a discovery engine that transforms messy biological data into real insights in minutes. Scientists ask questions in natural language, and Mithrl responds with analysis, novel targets, hypotheses, and patent-ready reports.

Our traction speaks for itself:

ABOUT THE ROLE

We are looking for a Lead Bioinformatics Pipeline Engineer to build and scale Mithrl’s multi modal scientific processing pipelines. You will own the workflows that transform raw biological data into clean, reproducible outputs that power Mithrl’s AI Co-Scientist. These workflows include microarray, imaging, spatial transcriptomics, genomics, epigenomics, flow cytometry, and more.

This role sits at the center of our technical stack. You will architect Nextflow and nf-core style pipelines, implement modality-specific validation and QC layers, and collaborate with the Tabular Data Team and Knowledge Curation Team to ensure downstream data harmonization, variable ID mapping, and schema alignment. Your work ensures that scientists can ask questions and receive accurate data-backed answers instantly.

If you enjoy building robust scientific workflows and want to work on high impact problems, you will thrive here.

WHAT YOU WILL DO

WHAT YOU BRING

Required Qualifications

Nice to Have

WHAT YOU WILL LOVE AT MITHRL

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

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