QA Engineer, Scientific Workflows

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.

Responsibilities

• 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
• Build CI workflows that run end to end tests on every commit and catch scientific and computational regressions
• Set up monitoring and alerting systems that track the health, performance, and scientific integrity of product modules
• Create 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
• Build a culture of scientific correctness and software reliability throughout the engineering and product teams

Requirements

• 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

Qualifications

• 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
• 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 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

What You Will Love

• 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 workflows
• Team: 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

Benefits

• Comprehensive PPO health coverage through Anthem (medical, dental, and vision)
• 401(k) with top-tier plans

Pay

$150K - $200K