ML Engineer, Biological Analysis & Simulation

Mithrl•San Francisco, CA

10d•Onsite

About The Position

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. You will develop the reusable analysis modules that Mithrl runs for every dataset, and you will design multi step agentic workflows that combine statistical analysis, biological reasoning, and computational modeling. You will also integrate and experiment with simulation tools for small molecule discovery, such as ADMET prediction, docking scoring, Boltzmann generators and related computational chemistry engines. 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.

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

Nice To Haves

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

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