Develops and leads production machine learning and image processing solutions for neurovascular OCT and angiographic medical imaging. Responsibilities span algorithm research, prototyping, software architecture, implementation, testing, validation, deployment, and maintenance within regulated medical device systems. The role provides technical mentorship, contributes to ML frameworks and infrastructure, collaborates cross-functionally, performs code reviews, and supports quality, documentation, and compliance initiatives.
Description
Role Summary
The Staff Machine Learning Software Engineer will play a key role in the development of advanced image processing and machine learning solutions for neurovascular Optical Coherence Tomography and angiographic imaging applications. This position spans the full development lifecycle, from early-stage feasibility investigations and algorithm prototyping through productization, verification, validation, and deployment within regulated medical device software systems. The successful candidate will provide technical leadership in image processing and machine learning initiatives and contribute to the architecture, design, development, and maintenance of ML-enabled software solutions within the company's imaging platform.
Essential Responsibilities
- Evaluate and develop image processing methodologies for image reconstruction, segmentation, registration, classification, and detection tasks, and quantitative image analysis.
- Investigate and assess traditional image processing, computer vision, and machine learning approaches to address clinical and product requirements.
- Design, implement, optimize, and maintain production-quality image processing and machine learning algorithms.
- Collaborate closely with software engineers, scientists, clinical experts, and product stakeholders throughout the development process.
- Contribute to the design and evolution of machine learning development frameworks, infrastructure, and best practices.
- Develop, debug, test, and optimize software components and machine learning pipelines.
- Support the maintenance and enhancement of internal software tools, datasets, and development utilities.
- Participate in software architecture, design reviews, and technical planning activities.
- Conduct code reviews and contribute to software quality, reliability, and maintainability initiatives.
- Evaluate and integrate third-party and off-the-shelf (OTS) software components when appropriate.
- Follow established quality system processes, standard operating procedures, and software development practices, including the creation and maintenance of required documentation.
- Provide technical guidance and mentorship to machine learning engineers and other software team members.
- Stay current with emerging technologies and advances in machine learning, computer vision, and medical imaging.
- Perform other duties as assigned.
Experience & Qualifications
Required qualifications
- M.S. or Ph.D. in Computer Science, Computer Engineering, Software Engineering, Biomedical Engineering, or a related technical field, or equivalent industry experience.
- Minimum of 8 years of experience developing image processing and machine learning solutions, preferably in medical imaging or regulated healthcare environments.
- Strong expertise in one or more machine learning frameworks. PyTorch preferred.
- Strong proficiency in Python and scientific computing ecosystems.
- Demonstrated experience developing and deploying traditional image processing and computer vision algorithms.
- Experience with software development best practices, including version control systems such as Git.
- Strong analytical, problem-solving, and debugging skills.
- Excellent communication and cross-functional collaboration abilities.
Preferred qualifications
- Experience with medical imaging platforms and toolkits such as OpenCV, ITK, VTK, MONAI, or similar frameworks.
- Experience with X-ray imaging systems for angiography applications.
- Experience with cloud-based machine learning workflows and MLOps practices.
- Knowledge of cybersecurity principles and secure software development practices for medical devices.
- Experience applying Good Machine Learning Practice (GMLP) principles and working within regulated medical device development environments.
- Familiarity with FDA, EU MDR, IEC 62304, ISO 13485, ISO 14971, IEC 81001-5-1, and related medical device software standards and regulations.
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