{"schemaVersion":"jobsearcher.job.v1","id":"95acd2e2f17e0e84fac50df3","url":"https://jobsearcher.com/jobs/95acd2e2f17e0e84fac50df3","canonicalUrl":"https://jobsearcher.com/jobs/95acd2e2f17e0e84fac50df3","title":"Machine Learning Engineer","description":"Position OverviewWe are seeking an experienced contractor with expertise in AI rapid prototyping, predictive modeling, and machine learning to support the DAISAE platform and predictive analytics subteams within the RDE 9 program.This role focuses on developing shared data and technical foundations, including ontologies and knowledge graphs, prototyping agentic AI capabilities, and advancing predictive models to support drug safety risk prediction throughout the product lifecycle.Key ResponsibilitiesAI Prototyping & MCP Tool DevelopmentExplore, evaluate, and rapidly prototype emerging AI tools and agentic AI capabilitiesDevelop Model Context Protocol (MCP) tools and AI agent integrations for the DAISAE platformPredictive Modeling & AnalyticsBuild and refine predictive models using multimodal datasets, including in vitro and in vivo data, omics, clinical trial data, real-world data (RWD), and spontaneous safety reportsSupport drug safety risk prediction, from early molecule-level evaluation through late-stage development and post-marketing patient safetyArchitecture & Platform DesignTranslate feasibility assessments and prototype evaluations into architectural designs and platform requirementsContribute to shared data and technical foundations, including ontologies and knowledge graphsCollaboration & Technical GovernanceDevelop reusable technical capabilities through agile prototyping before transitioning components to Roche Digital Tech (RDT) for formal validation, compliance, and production rolloutCollaborate with data scientists, safety scientists, and RDT technical partners to align technical execution with business prioritiesRequired Qualifications & ExperienceEducationMSc or PhD in Data Science, Computer Science, Computational Biology, Bioinformatics, Biostatistics, Epidemiology, or a related quantitative fieldTechnical ExpertiseStrong expertise in predictive modeling, machine learning, and AI prototypingHands-on experience developing agentic AI systems, large language model (LLM) tools, and MCP toolsProficiency in working with biomedical datasets, such as omics, clinical trial data, real-world data, or in vitro/in vivo dataStrong software engineering skills tailored to data science, with an agile prototyping mindsetDomain KnowledgeExperience in pharmacovigilance, drug safety, toxicology, or quantitative risk management is highly desirablePersonal AttributesAn AI-native approach to problem-solving and the ability to adapt to rapidly evolving AI frameworksProactive mindset and strong communication skills for working in global, cross-functional teams","company":"Aequor Information Technologies","rawCompany":"aequor information technologies","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-10-28T10:10:01.152Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"19-1029.01","title":"Bioinformatics Scientists","slug":"bioinformatics-scientists"}],"industries":[{"code":"541714","title":"Research and Development in Biotechnology (except Nanobiotechnology)","slug":"research-and-development-in-biotechnology-except-nanobiotechnology"},{"code":"541715","title":"Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)","slug":"research-and-development-in-the-physical-engineering-and-life-sciences-except-nanotechnology-and-biotechnology"},{"code":"541990","title":"All Other Professional, Scientific, and Technical Services","slug":"all-other-professional-scientific-and-technical-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Engineer","description":"Position OverviewWe are seeking an experienced contractor with expertise in AI rapid prototyping, predictive modeling, and machine learning to support the DAISAE platform and predictive analytics subteams within the RDE 9 program.This role focuses on developing shared data and technical foundations, including ontologies and knowledge graphs, prototyping agentic AI capabilities, and advancing predictive models to support drug safety risk prediction throughout the product lifecycle.Key ResponsibilitiesAI Prototyping & MCP Tool DevelopmentExplore, evaluate, and rapidly prototype emerging AI tools and agentic AI capabilitiesDevelop Model Context Protocol (MCP) tools and AI agent integrations for the DAISAE platformPredictive Modeling & AnalyticsBuild and refine predictive models using multimodal datasets, including in vitro and in vivo data, omics, clinical trial data, real-world data (RWD), and spontaneous safety reportsSupport drug safety risk prediction, from early molecule-level evaluation through late-stage development and post-marketing patient safetyArchitecture & Platform DesignTranslate feasibility assessments and prototype evaluations into architectural designs and platform requirementsContribute to shared data and technical foundations, including ontologies and knowledge graphsCollaboration & Technical GovernanceDevelop reusable technical capabilities through agile prototyping before transitioning components to Roche Digital Tech (RDT) for formal validation, compliance, and production rolloutCollaborate with data scientists, safety scientists, and RDT technical partners to align technical execution with business prioritiesRequired Qualifications & ExperienceEducationMSc or PhD in Data Science, Computer Science, Computational Biology, Bioinformatics, Biostatistics, Epidemiology, or a related quantitative fieldTechnical ExpertiseStrong expertise in predictive modeling, machine learning, and AI prototypingHands-on experience developing agentic AI systems, large language model (LLM) tools, and MCP toolsProficiency in working with biomedical datasets, such as omics, clinical trial data, real-world data, or in vitro/in vivo dataStrong software engineering skills tailored to data science, with an agile prototyping mindsetDomain KnowledgeExperience in pharmacovigilance, drug safety, toxicology, or quantitative risk management is highly desirablePersonal AttributesAn AI-native approach to problem-solving and the ability to adapt to rapidly evolving AI frameworksProactive mindset and strong communication skills for working in global, cross-functional teams","datePosted":"2026-10-28T10:10:01.152Z","dateModified":"2026-10-28T10:10:01.152Z","hiringOrganization":{"@type":"Organization","name":"Aequor Information Technologies","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"95acd2e2f17e0e84fac50df3"},"url":"https://jobsearcher.com/jobs/95acd2e2f17e0e84fac50df3"}}