ML Engineer, Discovery Applications

This range is provided by Mithrl. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range $150,000.00/yr - $240,000.00/yr 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 analysis, novel targets, hypotheses, and patent-ready reports. No coding. No waiting. No bioinformatics bottlenecks. We are one of the fastest growing tech bio companies in the Bay Area with 12x year over year revenue growth. Our platform is used across three continents by leading biotechs and big pharmas. We power breakthroughs from early target discovery to mechanism-of-action. And we are just getting started. ABOUT THE ROLE We are hiring an ML Engineer, Discovery Applications to build the high level, end-to-end scientific workflows that power real bench to bench decision making inside the Mithrl platform. This role focuses on building the application layer on top of the AI Co-Scientist. Your work will shape how scientists discover biomarkers, identify and validate targets, design experiments, and run early discovery programs that extend all the way to IND-enabling work. This role requires a deep understanding of the discovery and preclinical development cycle. You should understand how research teams move from early target hypotheses to biomarker strategy, hit identification, hit to lead, lead optimization, and preclinical validation. Your applications will support decision making across this entire arc and will be consumed directly by scientists and program teams. You will design multi step workflows that combine analysis modules, ML models, domain logic, and agentic reasoning into complete applications. These applications cover biomarker discovery, target ID, target validation, small molecule hit identification and optimization, and gene therapy workflows. You will also extend applications to support new data modalities as our platform expands. WHAT YOU WILL DO Build full discovery applications that support biomarker identification, target discovery, target validation, small molecule design workflows, and gene therapy programs Stand up new analyses that support application logic and improve or extend the existing analysis suite Create multi step reasoning flows that integrate ML models, statistical methods, pathway context, simulation tools, and biological domain logic Design application specific workflows for compound evaluation, program prioritization, and multi modal evidence integration Extend existing applications to incorporate new data modalities and new analysis routines Build reusable frameworks for Design of Experiments across biomarker discovery, target ID, validation, small molecule programs, and gene therapy Implement and improve the AI systems that orchestrate and chain analyses into coherent applications used directly by scientists Collaborate closely with ML engineers, bioinformatics teams, and data ingestion teams to ensure workflows run on consistent data Validate scientific correctness and ensure applications produce accurate, reproducible, and interpretable results WHAT YOU BRING Required Qualifications Strong experience in ML, computational biology, scientific computing, or a related field Deep understanding of the drug discovery and preclinical development cycle including early discovery, target identification, target validation, hit identification, hit to lead, lead optimization, and IND-enabling work Experience building analytical workflows or application logic for biological or scientific data Familiarity with key discovery analysis methods such as differential expression, pathway analysis, clustering, enrichment, and target scoring Proficiency in Python and scientific computing libraries and comfort with building multi step workflows Ability to convert scientific questions into structured, reproducible workflows that support real decision making Strong communication skills and ability to collaborate with cross functional engineering and biology teams Nice to Have Experience building LLM powered agents or multi agent reasoning systems Experience with multi modal biological data integration Experience with computational chemistry tools such as docking or ADMET modeling Familiarity with biological ontologies, curated knowledge sources, or pathway databases Prior experience in a tech bio startup, biotech R&D group, or scientific software platform WHAT YOU WILL LOVE AT MITHRL High ownership and impact: You will build the decision making applications that scientists rely on throughout the discovery and preclinical process 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 Seniority level Entry level Employment type Full-time Job function Engineering and Information Technology Software Development Referrals increase your chances of interviewing at Mithrl by 2x Get notified about new Machine Learning Engineer jobs in San Francisco, CA. #J-18808-Ljbffr