Mithrl
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:
12X year-over-year revenue growth
Trusted by leading biotechs and big pharma across three continents
Driving real breakthroughs from target discovery to patient outcomes.
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
Build automated test infrastructure for data ingestion, analysis modules, discovery applications, and new product features
Develop scientific validation frameworks that check correctness and reproducibility of ML driven biological analyses
Establish CI workflows that run end to end tests on every commit and catch scientific and computational regressions
Build monitoring and alerting systems that track the health, performance, and scientific integrity of product modules
Design automated checks for omics workflows
Validate that responses generated by Mithrl align with biological logic and expectations from discovery and preclinical development
Work closely with ML engineers, data engineers, and application scientists to ensure scientific accuracy across releases
Maintain documentation, data fixtures, and gold standard datasets for regression testing
Support the development of QA processes that scale with rapid product growth and new analysis capabilities
Build a culture of scientific correctness and software reliability throughout the engineering and product teams
WHAT YOU BRING Required Qualifications
PhD in biology, computational biology, bioinformatics, systems biology, or a related discovery field
Deep understanding of the drug discovery and preclinical development lifecycle
Hands‑on experience working with omics data such as transcriptomics, RNA‑seq, proteomics, ATAC‑seq, single cell datasets, or imaging‑derived features
Ability to evaluate whether a result, analysis, or insight is scientifically correct based on domain knowledge
Familiarity with common discovery analyses such as differential expression, enrichment, pathway reasoning, target scoring, and feature importance
Experience with Python or similar languages and comfort with scientific computing workflows
Strong interest in software quality, reproducibility, and validation of ML driven scientific systems
Excellent communication skills and ability to partner with engineers and scientists
Nice to Have
Experience building automated tests or QA frameworks for scientific or ML systems
Experience with workflow engines, scientific pipelines, or reproducibility tools
Familiarity with CI tools and modern software development practices
Experience validating outputs of AI powered analysis tools
Previous work in a tech bio company or computational platform environment
WHAT YOU WILL LOVE AT MITHRL
High ownership: You will be the guardian of scientific correctness and reliability inside the AI Co-Scientist
Impact: You will work with cutting edge ML, multi modal data, and real discovery workflowsTeam: Join a tight-knit, talent-dense team of engineers, scientists, and builders
Culture: We value consistency, clarity, and hard work. We solve hard problems through focused daily execution
Speed: We ship fast (2x/week) and improve continuously based on real user feedback
Location: Beautiful SF office with a high-energy, in-person culture
Benefits: Comprehensive PPO health coverage through Anthem (medical, dental, and vision) + 401(k) with top-tier plans
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.
#J-18808-Ljbffr
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:
12X year-over-year revenue growth
Trusted by leading biotechs and big pharma across three continents
Driving real breakthroughs from target discovery to patient outcomes.
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
Build automated test infrastructure for data ingestion, analysis modules, discovery applications, and new product features
Develop scientific validation frameworks that check correctness and reproducibility of ML driven biological analyses
Establish CI workflows that run end to end tests on every commit and catch scientific and computational regressions
Build monitoring and alerting systems that track the health, performance, and scientific integrity of product modules
Design automated checks for omics workflows
Validate that responses generated by Mithrl align with biological logic and expectations from discovery and preclinical development
Work closely with ML engineers, data engineers, and application scientists to ensure scientific accuracy across releases
Maintain documentation, data fixtures, and gold standard datasets for regression testing
Support the development of QA processes that scale with rapid product growth and new analysis capabilities
Build a culture of scientific correctness and software reliability throughout the engineering and product teams
WHAT YOU BRING Required Qualifications
PhD in biology, computational biology, bioinformatics, systems biology, or a related discovery field
Deep understanding of the drug discovery and preclinical development lifecycle
Hands‑on experience working with omics data such as transcriptomics, RNA‑seq, proteomics, ATAC‑seq, single cell datasets, or imaging‑derived features
Ability to evaluate whether a result, analysis, or insight is scientifically correct based on domain knowledge
Familiarity with common discovery analyses such as differential expression, enrichment, pathway reasoning, target scoring, and feature importance
Experience with Python or similar languages and comfort with scientific computing workflows
Strong interest in software quality, reproducibility, and validation of ML driven scientific systems
Excellent communication skills and ability to partner with engineers and scientists
Nice to Have
Experience building automated tests or QA frameworks for scientific or ML systems
Experience with workflow engines, scientific pipelines, or reproducibility tools
Familiarity with CI tools and modern software development practices
Experience validating outputs of AI powered analysis tools
Previous work in a tech bio company or computational platform environment
WHAT YOU WILL LOVE AT MITHRL
High ownership: You will be the guardian of scientific correctness and reliability inside the AI Co-Scientist
Impact: You will work with cutting edge ML, multi modal data, and real discovery workflowsTeam: Join a tight-knit, talent-dense team of engineers, scientists, and builders
Culture: We value consistency, clarity, and hard work. We solve hard problems through focused daily execution
Speed: We ship fast (2x/week) and improve continuously based on real user feedback
Location: Beautiful SF office with a high-energy, in-person culture
Benefits: Comprehensive PPO health coverage through Anthem (medical, dental, and vision) + 401(k) with top-tier plans
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.
#J-18808-Ljbffr