ML Engineer, Biological Analysis & Simulation

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.

Responsibilities

• 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

Requirements

• 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

Qualifications

• Required Qualifications
• Nice to Have

What You Will Love

• 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

Compensation Range

$150K - $200K