ML Engineer, Biological Analysis & Simulation
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.
- 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 drug 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
- 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
- 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
- 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) + 401(k) with top-tier plans
Vacancy posted 1 day ago
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