ML Engineer, Biological Analysis & Simulation
Listed on 2026-01-02
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Research/Development
Data Scientist -
IT/Tech
Data Scientist, AI Engineer
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.
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.
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.
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 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
Required Qualifications
- 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…
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