Job Opportunities API

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