{"schemaVersion":"jobsearcher.job.v1","id":"5ac2a01d03cd4591cceba0a4","url":"https://jobsearcher.com/jobs/5ac2a01d03cd4591cceba0a4","canonicalUrl":"https://jobsearcher.com/jobs/5ac2a01d03cd4591cceba0a4","title":"Machine Learning Scientist","description":"Machine Learning ScientistCompensation: $230,000–$280,000 baseLocation: Hybrid or RemoteWork Authorization: No visa sponsorship availableCompany OverviewWe are partnering with a AI‑native therapeutics company applying frontier machine learning to understand human biology and improve clinical outcomes in oncology. The company has built one of the largest proprietary multimodal biological datasets in the industry and trains large-scale foundation models from scratch to predict therapeutic efficacy and identify patient populations most likely to benefit from treatment.Artificial intelligence is central to the company’s strategy. The team develops proprietary datasets, conducts original machine learning research, and applies advanced models directly to drug discovery.Position SummaryWe are seeking a Machine Learning Scientist to conduct original, high‑impact machine learning research and help develop the next generation of biological foundation models.This is a hands-on individual contributor role. The ideal candidate is a highly capable researcher who can independently formulate ideas, rapidly implement experiments, evaluate results, and clearly communicate findings to both technical and scientific audiences.This position emphasizes research quality, scientific rigor, and intellectual contribution rather than production engineering, people management, or infrastructure ownership.Key ResponsibilitiesDesign, implement, and train foundation models on large-scale multimodal biological datasetsDevelop novel machine learning approaches for integrating information across biological scales and measurement modalitiesDefine meaningful benchmark tasks and evaluation frameworks for foundation modelsRapidly prototype research ideas and identify the most informative experiments to runAnalyze experimental results rigorously and iterate based on findingsCollaborate closely with biologists, computational scientists, and ML researchersEvaluate modern AI techniques, including large language models, for internal scientific workflowsCommunicate research results clearly to both technical and non-technical stakeholdersOwn research projects end-to-end, from initial concept through execution and conclusionsContribute to publications, conference presentations, and external scientific engagement as appropriateRequired QualificationsResearch BackgroundDemonstrated excellence in original machine learning research, evidenced by:First-author publications at leading conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL, EMNLP), orSignificant research contributions within top-tier industry research labsStrong ability to independently drive research from idea to validationProven capability to design experiments, build models, define evaluations, and interpret resultsTechnical SkillsDeep knowledge of modern machine learning methods and architecturesStrong experience implementing research models in PyTorchFamiliarity with self-supervised learning, representation learning, and generative modeling approachesEducationPhD strongly preferred in:Computer ScienceMachine Learning / Artificial IntelligenceStatisticsApplied MathematicsComputational NeurosciencePhysics or other highly quantitative disciplinesExceptional candidates without a PhD may be considered with a compelling research track recordPreferred Technical AreasFoundation ModelsSelf-Supervised Learning and Representation LearningMultimodal LearningComputer VisionLarge Language ModelsGenerative Models (Diffusion, Flow Matching, Autoregressive Models)Scientific Machine LearningCandidates are expected to write robust, high-quality research code, but this role is fundamentally focused on scientific insight and model development, not large-scale production systems.Why JoinWork on frontier machine learning research applied to real-world biological problemsTrain large foundation models on proprietary, purpose-built multimodal datasetsCollaborate with a highly technical, interdisciplinary teamOperate in an environment where AI is core to the company’s missionMake a meaningful impact on scientific discovery and patient outcomes","company":"Harnham","rawCompany":"harnham","city":"Menlo Park","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-06-26T11:33:12.251Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"},{"code":"19-1029.01","title":"Bioinformatics Scientists","slug":"bioinformatics-scientists"}],"industries":[{"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":"541714","title":"Research and Development in Biotechnology (except Nanobiotechnology)","slug":"research-and-development-in-biotechnology-except-nanobiotechnology"},{"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 Scientist","description":"Machine Learning ScientistCompensation: $230,000–$280,000 baseLocation: Hybrid or RemoteWork Authorization: No visa sponsorship availableCompany OverviewWe are partnering with a AI‑native therapeutics company applying frontier machine learning to understand human biology and improve clinical outcomes in oncology. The company has built one of the largest proprietary multimodal biological datasets in the industry and trains large-scale foundation models from scratch to predict therapeutic efficacy and identify patient populations most likely to benefit from treatment.Artificial intelligence is central to the company’s strategy. The team develops proprietary datasets, conducts original machine learning research, and applies advanced models directly to drug discovery.Position SummaryWe are seeking a Machine Learning Scientist to conduct original, high‑impact machine learning research and help develop the next generation of biological foundation models.This is a hands-on individual contributor role. The ideal candidate is a highly capable researcher who can independently formulate ideas, rapidly implement experiments, evaluate results, and clearly communicate findings to both technical and scientific audiences.This position emphasizes research quality, scientific rigor, and intellectual contribution rather than production engineering, people management, or infrastructure ownership.Key ResponsibilitiesDesign, implement, and train foundation models on large-scale multimodal biological datasetsDevelop novel machine learning approaches for integrating information across biological scales and measurement modalitiesDefine meaningful benchmark tasks and evaluation frameworks for foundation modelsRapidly prototype research ideas and identify the most informative experiments to runAnalyze experimental results rigorously and iterate based on findingsCollaborate closely with biologists, computational scientists, and ML researchersEvaluate modern AI techniques, including large language models, for internal scientific workflowsCommunicate research results clearly to both technical and non-technical stakeholdersOwn research projects end-to-end, from initial concept through execution and conclusionsContribute to publications, conference presentations, and external scientific engagement as appropriateRequired QualificationsResearch BackgroundDemonstrated excellence in original machine learning research, evidenced by:First-author publications at leading conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL, EMNLP), orSignificant research contributions within top-tier industry research labsStrong ability to independently drive research from idea to validationProven capability to design experiments, build models, define evaluations, and interpret resultsTechnical SkillsDeep knowledge of modern machine learning methods and architecturesStrong experience implementing research models in PyTorchFamiliarity with self-supervised learning, representation learning, and generative modeling approachesEducationPhD strongly preferred in:Computer ScienceMachine Learning / Artificial IntelligenceStatisticsApplied MathematicsComputational NeurosciencePhysics or other highly quantitative disciplinesExceptional candidates without a PhD may be considered with a compelling research track recordPreferred Technical AreasFoundation ModelsSelf-Supervised Learning and Representation LearningMultimodal LearningComputer VisionLarge Language ModelsGenerative Models (Diffusion, Flow Matching, Autoregressive Models)Scientific Machine LearningCandidates are expected to write robust, high-quality research code, but this role is fundamentally focused on scientific insight and model development, not large-scale production systems.Why JoinWork on frontier machine learning research applied to real-world biological problemsTrain large foundation models on proprietary, purpose-built multimodal datasetsCollaborate with a highly technical, interdisciplinary teamOperate in an environment where AI is core to the company’s missionMake a meaningful impact on scientific discovery and patient outcomes","datePosted":"2026-06-26T11:33:12.251Z","dateModified":"2026-06-26T11:33:12.251Z","hiringOrganization":{"@type":"Organization","name":"Harnham","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Menlo Park","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"5ac2a01d03cd4591cceba0a4"},"url":"https://jobsearcher.com/jobs/5ac2a01d03cd4591cceba0a4"}}