{"schemaVersion":"jobsearcher.job.v1","id":"537b0d021ca0720bf482fcda","url":"https://jobsearcher.com/jobs/537b0d021ca0720bf482fcda","canonicalUrl":"https://jobsearcher.com/jobs/537b0d021ca0720bf482fcda","title":"MTS, Machine Learning","description":"Drug discovery is a prediction problem. Scientists design molecules that they predict will be potent, safe, and readily absorbed into the body, but ultimately lab experiments must be run to know whether these predictions are accurate. Each one of these experiments can take weeks or months to run, and as a result it costs millions of dollars and takes years to design a molecule that is ready for testing in humans.\n\nAt Inductive Bio, we're using AI to build in silico models that more accurately predict how molecules will behave in experiments, helping scientists make better decisions faster. Our ADMET/PK models have placed first in the world’s largest AI drug discovery competition for ADMET benchmarks three consecutive times, and our technology is already being applied across dozens of biopharma partnerships.\n\nBacked by leading technology and biotechnology investors including a16z, Lux, S32, and Obvious, our team brings together world-class expertise in machine learning and drug discovery.\n\nWe are seeking a Member of Technical Staff, Machine Learning to join our talented, ambitious, and kind team. You’ll innovate on ML methods, work closely with leading drug discovery scientists, and see your work applied directly to real drug programs. You’ll have significant ownership, impact, and opportunity to grow with the company.\n\nWhat you’ll do:\n\nDevelop machine learning models to predict molecular properties from chemical structures\n\nDevelop novel algorithms for generating ideas for new molecules\n\nBuild agents that can synthesize complex information from drug programs and apply that information strategically toward molecular optimization\n\nGet your hands dirty by diving deep into our unique, proprietary dataset to iterate on modeling ideas and improve model performance\n\nCollaborate closely with chemists and software engineers to integrate models into our software platform, which is used by drug discovery scientists across the industry\n\nBuild and optimize scalable infrastructure for model training, deployment, and monitoring\n\nEngage directly with our scientific users, incorporating their feedback into the product\n\nContribute meaningfully to product strategy and company direction\n\nWho you are:\n\nYou have 4+ years of experience as a Machine Learning Scientist, Machine Learning Engineer, Data Scientist, or similar role\n\nYou have a strong scientific background, ideally with a PhD in chemistry, biology, physics, or a related field\n\nYou have expertise in machine learning fundamentals, deep learning architectures, and evaluation approaches\n\nYou are proficient in standard Python-based ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn)\n\nYou are comfortable writing high-quality, reusable code and productionizing models for serving in the cloud\n\nYou are excited to dive deep into the science and practice of drug discovery\n\nYou have exceptional written and oral communication skills\n\nPreferred experience:\n\nYou have graduate-level knowledge of cell / molecular biology or biochemistry, and experience collaborating with wet lab scientists\n\nExperience with omics modeling (transcriptomics, proteomics, metabolomics, etc)\n\nExperience with high-content screening and signal processing from microscopy data\n\nWorking at Inductive\n\nAt Inductive Bio, we know that the people on the team are what make us great. We offer competitive salary and equity-based compensation; comprehensive healthcare benefits (including dental and vision); and the opportunity to grow along with a rapidly scaling company. We are a passionate, kind, and mature team. Working at a fast growing startup is not always a 9-5 job, but we believe that our employees should have full lives beyond their career.\n\nCompensation Range: $180K - $250K","company":"Inductive Bio","rawCompany":"inductive bio","city":"Denver","state":"CO","isRemote":false,"isActive":false,"createdAt":"2026-09-14T09:56:35.733Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"19-1029.01","title":"Bioinformatics Scientists","slug":"bioinformatics-scientists"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-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":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"MTS, Machine Learning","description":"Drug discovery is a prediction problem. Scientists design molecules that they predict will be potent, safe, and readily absorbed into the body, but ultimately lab experiments must be run to know whether these predictions are accurate. Each one of these experiments can take weeks or months to run, and as a result it costs millions of dollars and takes years to design a molecule that is ready for testing in humans.\n\nAt Inductive Bio, we're using AI to build in silico models that more accurately predict how molecules will behave in experiments, helping scientists make better decisions faster. Our ADMET/PK models have placed first in the world’s largest AI drug discovery competition for ADMET benchmarks three consecutive times, and our technology is already being applied across dozens of biopharma partnerships.\n\nBacked by leading technology and biotechnology investors including a16z, Lux, S32, and Obvious, our team brings together world-class expertise in machine learning and drug discovery.\n\nWe are seeking a Member of Technical Staff, Machine Learning to join our talented, ambitious, and kind team. You’ll innovate on ML methods, work closely with leading drug discovery scientists, and see your work applied directly to real drug programs. You’ll have significant ownership, impact, and opportunity to grow with the company.\n\nWhat you’ll do:\n\nDevelop machine learning models to predict molecular properties from chemical structures\n\nDevelop novel algorithms for generating ideas for new molecules\n\nBuild agents that can synthesize complex information from drug programs and apply that information strategically toward molecular optimization\n\nGet your hands dirty by diving deep into our unique, proprietary dataset to iterate on modeling ideas and improve model performance\n\nCollaborate closely with chemists and software engineers to integrate models into our software platform, which is used by drug discovery scientists across the industry\n\nBuild and optimize scalable infrastructure for model training, deployment, and monitoring\n\nEngage directly with our scientific users, incorporating their feedback into the product\n\nContribute meaningfully to product strategy and company direction\n\nWho you are:\n\nYou have 4+ years of experience as a Machine Learning Scientist, Machine Learning Engineer, Data Scientist, or similar role\n\nYou have a strong scientific background, ideally with a PhD in chemistry, biology, physics, or a related field\n\nYou have expertise in machine learning fundamentals, deep learning architectures, and evaluation approaches\n\nYou are proficient in standard Python-based ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn)\n\nYou are comfortable writing high-quality, reusable code and productionizing models for serving in the cloud\n\nYou are excited to dive deep into the science and practice of drug discovery\n\nYou have exceptional written and oral communication skills\n\nPreferred experience:\n\nYou have graduate-level knowledge of cell / molecular biology or biochemistry, and experience collaborating with wet lab scientists\n\nExperience with omics modeling (transcriptomics, proteomics, metabolomics, etc)\n\nExperience with high-content screening and signal processing from microscopy data\n\nWorking at Inductive\n\nAt Inductive Bio, we know that the people on the team are what make us great. We offer competitive salary and equity-based compensation; comprehensive healthcare benefits (including dental and vision); and the opportunity to grow along with a rapidly scaling company. We are a passionate, kind, and mature team. Working at a fast growing startup is not always a 9-5 job, but we believe that our employees should have full lives beyond their career.\n\nCompensation Range: $180K - $250K","datePosted":"2026-09-14T09:56:35.733Z","dateModified":"2026-09-14T09:56:35.733Z","hiringOrganization":{"@type":"Organization","name":"Inductive Bio","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Denver","addressRegion":"CO","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"537b0d021ca0720bf482fcda"},"url":"https://jobsearcher.com/jobs/537b0d021ca0720bf482fcda"}}