WHAT YOU WILL DOBuild full discovery applications that support biomarker identification, target discovery, target validation, small molecule design workflows, and gene therapy programsStand up new analyses that support application logic and improve or extend the existing analysis suiteCreate multi step reasoning flows that integrate ML models, statistical methods, pathway context, simulation tools, and biological domain logicDesign application specific workflows for compound evaluation, program prioritization, and multi modal evidence integrationExtend existing applications to incorporate new data modalities and new analysis routinesBuild reusable frameworks for Design of Experiments across biomarker discovery, target ID, validation, small molecule programs, and gene therapyImplement and improve the AI systems that orchestrate and chain analyses into coherent applications used directly by scientistsCollaborate closely with ML engineers, bioinformatics teams, and data ingestion teams to ensure workflows run on consistent dataValidate scientific correctness and ensure applications produce accurate, reproducible, and interpretable resultsWHAT YOU BRINGRequired QualificationsStrong experience in ML, computational biology, scientific computing, or a related fieldDeep understanding of the drug discovery and preclinical development cycle including early discovery, target identification, target validation, hit identification, hit to lead, lead optimization, and IND-enabling workExperience building analytical workflows or application logic for biological or scientific dataFamiliarity with key discovery analysis methods such as differential expression, pathway analysis, clustering, enrichment, and target scoringProficiency in Python and scientific computing libraries and comfort with building multi step workflowsAbility to convert scientific questions into structured, reproducible workflows that support real decision makingStrong communication skills and ability to collaborate with cross functional engineering and biology teamsNice to HaveExperience building LLM powered agents or multi agent reasoning systemsExperience with multi modal biological data integrationExperience with computational chemistry tools such as docking or ADMET modelingFamiliarity with biological ontologies, curated knowledge sources, or pathway databasesPrior experience in a tech bio startup, biotech R&D group, or scientific software platformWHAT YOU WILL LOVE AT MITHRLHigh ownership and impact: You will build the decision making applications that scientists rely on throughout the discovery and preclinical processTeam: Join a tight-knit, talent-dense team of engineers, scientists, and buildersCulture: We value consistency, clarity, and hard work. Your work will shape how scientists discover biomarkers, identify and validate targets, design experiments, and run early discovery programs that extend all the way to IND-enabling work.