Sr. Machine Learning Engineer at Neosoft LLC

City of Pewaukee, Wisconsin, United States -

Full Time

Start Date

Immediate

Expiry Date

15 Jun, 26

Salary

178000.0

Posted On

17 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Deep Learning, PyTorch, Python, Medical Imaging, MONAI, SimpleITK, NiBabel, TorchIO, Convolutional Neural Networks, Vision Transformers, 3D Imaging Models, Model Deployment, GPU Inference, Regulatory Compliance, Mentorship

Industry

Software Development

Description

Description Position 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. Essential Responsibilities: Develop state-of-the-art ML/DL models for segmentation, quantification, classification, and image-based predictions using cardiac MRI data. Conduct research experiments, evaluate new model architectures, and optimize algorithms for performance, speed, and robustness. Prepare datasets, including preprocessing, augmentation, and quality control of medical imaging data. Explore and implement foundation-model techniques such as self-supervised learning and transfer learning. Convert research prototypes into production-ready models following software engineering best practices. Optimize models for GPU inference, scalability, and low-latency processing. Implement model serving pipelines, APIs, continuous integration/continuous deployment, and performance monitoring. Collaborate with DevOps and engineering teams on integration with suiteHEART and cloud or on-premises infrastructure. Contribute to documentation required for software as a medical device, including AI design documents, risk analyses, verification and validation plans, and model change protocols. Ensure ML pipeline traceability, reproducibility, and proper dataset versioning. Support regulatory submissions with technical justifications and performance reporting. Partner with product management to translate clinical requirements into ML features. Provide mentorship to junior ML engineers and interns. Requirements Necessary skills and experience: Master’s or PhD in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field. Five or more years of experience developing machine learning or deep learning models in production environments. Expertise in Python, PyTorch, and medical imaging libraries such as MONAI, SimpleITK, NiBabel, or TorchIO. Strong background in convolutional neural networks, vision transformers, 3D imaging models, and statistical evaluation methods. Familiarity with regulatory expectations for machine learning in medical devices, including FDA Good Machine Learning Practice and SaMD guidelines. General characteristics needed for success in position: Strong communication skills for explaining technical concepts to non-technical stakeholders. Ability to work in a fast-paced environment with changing priorities. Strong problem-solving skills, innovative mindset, and attention to detail. Reporting to this position: No direct reports Physical 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. Physical 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. Work Environment: The noise level in the work environment is minimal.

Responsibilities

The Senior Machine Learning Engineer will design, develop, validate, and deploy advanced ML/DL models for cardiac MRI analysis, focusing on segmentation, quantification, and classification tasks. This involves conducting research, optimizing algorithms, implementing production pipelines, and ensuring compliance with medical device regulatory requirements.