{"schemaVersion":"jobsearcher.job.v1","id":"4ace6c3da50371c5a7a16f26","url":"https://jobsearcher.com/jobs/4ace6c3da50371c5a7a16f26","canonicalUrl":"https://jobsearcher.com/jobs/4ace6c3da50371c5a7a16f26","title":"Sr. Machine Learning Engineer","description":"Description:\nPosition Summary: The Senior Machine Learning Engineer is responsible for designing, developing, validating, and deploying advanced machine learning and deep learning models to support NeoSoft’s cardiac MRI analysis platform. This role works closely with software engineers, data scientists, clinicians, and regulatory teams to build robust, reliable, and explainable ML systems suitable for clinical environments and medical device regulatory requirements.\nEssential Responsibilities:\nDevelop state-of-the-art ML/DL models for segmentation, quantification, classification, and image-based predictions using cardiac MRI data.\nConduct research experiments, evaluate new model architectures, and optimize algorithms for performance, speed, and robustness.\nPrepare datasets, including preprocessing, augmentation, and quality control of medical imaging data.\nExplore and implement foundation-model techniques such as self-supervised learning and transfer learning.\nConvert research prototypes into production-ready models following software engineering best practices.\nOptimize models for GPU inference, scalability, and low-latency processing.\nImplement model serving pipelines, APIs, continuous integration/continuous deployment, and performance monitoring.\nCollaborate with DevOps and engineering teams on integration with suiteHEART and cloud or on-premises infrastructure.\nContribute to documentation required for software as a medical device, including AI design documents, risk analyses, verification and validation plans, and model change protocols.\nEnsure ML pipeline traceability, reproducibility, and proper dataset versioning.\nSupport regulatory submissions with technical justifications and performance reporting.\nPartner with product management to translate clinical requirements into ML features.\nProvide mentorship to junior ML engineers and interns.\nRequirements:\nNecessary skills and experience:\nMaster’s or PhD in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field.\nFive or more years of experience developing machine learning or deep learning models in production environments.\nExpertise in Python, PyTorch, and medical imaging libraries such as MONAI, SimpleITK, NiBabel, or TorchIO.\nStrong background in convolutional neural networks, vision transformers, 3D imaging models, and statistical evaluation methods.\nFamiliarity with regulatory expectations for machine learning in medical devices, including FDA Good Machine Learning Practice and SaMD guidelines.\nGeneral characteristics needed for success in position:\nStrong communication skills for explaining technical concepts to non-technical stakeholders.\nAbility to work in a fast-paced environment with changing priorities.\nStrong problem-solving skills, innovative mindset, and attention to detail.\nReporting to this position: No direct reports\nPhysical demands and work environment: The physical demands and work environment characteristics described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.\nPhysical demands: While performing duties of job, employee is frequently required to type, sit, stand; walk; use hands, talk and hear; occasionally reach with hands and arms. Employee must occasionally lift and/or move up to 10 pounds. Specific vision abilities required by the job include close vision, distance vision, color vision, peripheral vision, depth perception, and the ability to adjust focus.\nWork Environment: The noise level in the work environment is minimal.","company":"Neosoft","rawCompany":"neosoft","city":"Pewaukee","state":"WI","isRemote":false,"isActive":false,"createdAt":"2026-04-14T11:22:39.142Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"}],"industries":[{"code":"334510","title":"Electromedical and Electrotherapeutic Apparatus Manufacturing","slug":"electromedical-and-electrotherapeutic-apparatus-manufacturing"},{"code":"622110","title":"General Medical and Surgical Hospitals","slug":"general-medical-and-surgical-hospitals"},{"code":"622310","title":"Specialty (except Psychiatric and Substance Abuse) Hospitals","slug":"specialty-except-psychiatric-and-substance-abuse-hospitals"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Sr. Machine Learning Engineer","description":"Description:\nPosition Summary: The Senior Machine Learning Engineer is responsible for designing, developing, validating, and deploying advanced machine learning and deep learning models to support NeoSoft’s cardiac MRI analysis platform. This role works closely with software engineers, data scientists, clinicians, and regulatory teams to build robust, reliable, and explainable ML systems suitable for clinical environments and medical device regulatory requirements.\nEssential Responsibilities:\nDevelop state-of-the-art ML/DL models for segmentation, quantification, classification, and image-based predictions using cardiac MRI data.\nConduct research experiments, evaluate new model architectures, and optimize algorithms for performance, speed, and robustness.\nPrepare datasets, including preprocessing, augmentation, and quality control of medical imaging data.\nExplore and implement foundation-model techniques such as self-supervised learning and transfer learning.\nConvert research prototypes into production-ready models following software engineering best practices.\nOptimize models for GPU inference, scalability, and low-latency processing.\nImplement model serving pipelines, APIs, continuous integration/continuous deployment, and performance monitoring.\nCollaborate with DevOps and engineering teams on integration with suiteHEART and cloud or on-premises infrastructure.\nContribute to documentation required for software as a medical device, including AI design documents, risk analyses, verification and validation plans, and model change protocols.\nEnsure ML pipeline traceability, reproducibility, and proper dataset versioning.\nSupport regulatory submissions with technical justifications and performance reporting.\nPartner with product management to translate clinical requirements into ML features.\nProvide mentorship to junior ML engineers and interns.\nRequirements:\nNecessary skills and experience:\nMaster’s or PhD in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field.\nFive or more years of experience developing machine learning or deep learning models in production environments.\nExpertise in Python, PyTorch, and medical imaging libraries such as MONAI, SimpleITK, NiBabel, or TorchIO.\nStrong background in convolutional neural networks, vision transformers, 3D imaging models, and statistical evaluation methods.\nFamiliarity with regulatory expectations for machine learning in medical devices, including FDA Good Machine Learning Practice and SaMD guidelines.\nGeneral characteristics needed for success in position:\nStrong communication skills for explaining technical concepts to non-technical stakeholders.\nAbility to work in a fast-paced environment with changing priorities.\nStrong problem-solving skills, innovative mindset, and attention to detail.\nReporting to this position: No direct reports\nPhysical demands and work environment: The physical demands and work environment characteristics described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.\nPhysical demands: While performing duties of job, employee is frequently required to type, sit, stand; walk; use hands, talk and hear; occasionally reach with hands and arms. Employee must occasionally lift and/or move up to 10 pounds. Specific vision abilities required by the job include close vision, distance vision, color vision, peripheral vision, depth perception, and the ability to adjust focus.\nWork Environment: The noise level in the work environment is minimal.","datePosted":"2026-04-14T11:22:39.142Z","dateModified":"2026-04-14T11:22:39.142Z","hiringOrganization":{"@type":"Organization","name":"Neosoft","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Pewaukee","addressRegion":"WI","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"4ace6c3da50371c5a7a16f26"},"url":"https://jobsearcher.com/jobs/4ace6c3da50371c5a7a16f26"}}