ML Engineer, Biological Analysis - San Francisco - Mithrl

    Mithrl
    Mithrl San Francisco

    3 days ago

    Description

    ML Engineer, Analysis And Simulation

    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 an ML Engineer, Analysis and Simulation to build the core analytical and reasoning layer behind the Mithrl AI Co-Scientist. Your work will define how the AI interprets biological datasets, generates scientific conclusions, and orchestrates downstream simulation tools for drug discovery.

    This is the role that makes the AI Co-Scientist smart. If you have a strong background in ML, computational biology, and scientific analysis workflows, and you want to shape how AI reasons about biological systems, this is an exceptional opportunity.

    What You Will Do

    • Build AI driven analysis agents that perform biological reasoning across a wide range of datasets
    • Develop the standard analysis suite for each dataset, including modules for differential expression, pathway analysis, feature importance, clustering, scoring, enrichment, and mechanism-of-action interpretation
    • Build multi step workflows that combine ML models, statistical logic, and biological knowledge to produce high confidence insights
    • Design and implement agentic reasoning strategies that allow Mithrl to run dozens analyses per dataset and synthesize the outputs into a coherent scientific narrative
    • Integrate simulation and modeling tools for small molecule discovery, including ADMET prediction, docking scoring, generative chemistry tools, structure based modeling, and related computational frameworks
    • Collaborate with the data engineering, bioinformatics, and curation teams to ensure analysis modules operate on clean and consistent data
    • Validate results, benchmark pipelines, and ensure scientific accuracy and reproducibility of all analyses
    • Contribute to the long term architecture for how the AI Co-Scientist performs reasoning, hypothesis testing, and simulation

    What You Bring

    • Strong experience in machine learning, computational biology, or a related scientific ML field
    • Experience developing analysis modules for biological or scientific datasets
    • Familiarity with common techniques in target discovery, gene expression analysis, pathway inference, clustering, or statistical modeling
    • Hands-on experience with computational chemistry or simulation tools, such as ADMET models, docking, binding prediction, or molecular generative models
    • Proficiency in Python and scientific computing libraries
    • Experience designing multi step reasoning or workflow based ML pipelines
    • Ability to translate messy scientific questions into structured ML or analytical workflows
    • Strong communication skills and comfort collaborating with cross functional scientific and engineering teams

    Nice To Have

    • Experience with LLM powered scientific agents or multi agent architectures
    • Familiarity with phenotype based discovery, multi modal integration, or systems biology
    • Background in computational chemistry or structure based drug discovery
    • Experience with biological ontologies, curated knowledge graphs, or pathway databases
    • Prior experience in a tech bio company, biotech R&D group, or scientific platform team

    What You Will Love At Mithrl

    • High ownership: You will define how the AI Co-Scientist thinks and reasons about biology
    • Impact: You will work at the intersection of ML, biology, and simulation, with direct impact on real discovery programs
    • 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 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.

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