QA Engineer, Scientific Workflows

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 insights in minutes. Scientists ask questions in natural language, and Mithrl responds with real analysis, novel targets, hypotheses, and patent-ready reports.

Our traction speaks for itself:

ABOUT THE ROLE

We are hiring a QA Engineer, Scientific Software to build the test, validation, and monitoring infrastructure that guarantees the correctness and reliability of the Mithrl AI Co-Scientist. This role requires a PhD-level scientist or computational biologist who understands the drug development lifecycle and who has hands-on experience with omics data. Without this scientific foundation, it is not possible to evaluate whether Mithrl’s outputs are biologically meaningful.

You will create automated tests for analysis workflows, ingestion pipelines, and discovery applications. You will build CI systems that catch regressions early, set up monitoring and alerting for system behavior, and ensure that every module in Mithrl produces scientifically valid and reproducible outputs. This role bridges scientific understanding with software quality engineering and is critical for maintaining trust in Mithrl’s analysis engine.

If you are a scientist with a passion for product reliability, reproducibility, and validation of ML powered scientific tools, this is a uniquely impactful position.

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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