Senior Engineer, Health AI (Medical Imaging & Clinical Decision Support)

Boston Scientific•Maple Grove, MN

10h•$89,200 - $169,500

About The Position

As a leader in medical science for more than 40 years, we are committed to solving the challenges that matter most - united by a deep caring for human life. Our mission to advance science for life is about transforming lives through innovative medical solutions that improve patient lives, create value for our customers, and support our employees and the communities in which we operate. Now more than ever, we have a responsibility to apply those values to everything we do - as a global business and as a global corporate citizen. And if you're a natural problem-solver with the imagination, determination, and spirit to make a meaningful difference to people worldwide, we encourage you to apply and look forward to connecting with you! That is why we stand for inclusion, equality, and opportunity for all. By embracing the richness of our unique backgrounds and perspectives, we create a better, more rewarding place for our employees to work and reflect the patients, customers, and communities we serve. To ensure full implementation of its equal employment policy, the Company will continue to take steps to assure that recruitment, hiring, assignment, promotion, compensation, and all other personnel decisions are made and administered without regard to race, religion, color, national origin, citizenship, sex, sexual orientation, gender identity, gender expression, veteran status, age, mental or physical disability, genetic information or any other protected class. Please be advised that certain US based positions, including without limitation field sales and service positions that call on hospitals and/or health care centers, require acceptable proof of COVID-19 vaccination status. Candidates will be notified during the interview and selection process if the role(s) for which they have applied require proof of vaccination as a condition of employment. As employees of the Company, you will be expected to meet the ongoing requirements for your roles, including any new requirements, should the Company's policies or protocols change with regard to COVID-19 vaccination.

Requirements

Bachelor's degree in computer science, engineering, data science, biomedical engineering, or a related technical field, or equivalent practical experience.
Minimum of 7 years' experience in software engineering, machine learning engineering, or applied AI.
Minimum of 3 years' experience delivering machine learning-enabled products into production environments.
Demonstrated experience developing AI and machine learning solutions for healthcare, with a strong emphasis on medical imaging and or multimodal clinical data.
Clinical domain fluency, including the ability to understand disease-state context, clinical workflows, and translate clinical needs into algorithm requirements and validation plans.
Hands-on experience working with healthcare data such as DICOM imaging, radiology reports, EHR, HL7, FHIR, pathology, waveforms, or claims data, including associated privacy, security, labeling, and data quality considerations.
Strong programming skills in Python and experience with deep learning and machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn.
Production engineering experience building and operating machine learning-enabled services, including APIs or batch pipelines, containerization, CI/CD, and scalable deployment patterns.
Experience with model lifecycle management, including dataset and artifact versioning, performance and drift monitoring, and reliable retraining and release processes.
Experience working within regulated product development environments, including SaMD, design controls, documentation, traceability, and risk management, in partnership with Quality and Regulatory teams.
Strong communication and documentation skills, with the ability to align technical and non-technical stakeholders on requirements, design tradeoffs, risks, and validation evidence.
Direct experience delivering AI or machine learning as part of medical device or SaMD programs, including contribution to regulatory submissions or audit-ready documentation.
Familiarity with applicable standards and practices for regulated medical software and clinical evaluation, such as ISO 13485, ISO 14971, IEC 62304, IEC 62366, and GMLP.
Experience applying Responsible AI principles in healthcare, including bias and subgroup analysis, interpretability, uncertainty, and human-in-the-loop workflows.
Strong background in clinical informatics and workflow integration, including radiology or PACS integration and downstream clinical workflow impact.
Experience with cloud-native machine learning and MLOps platforms, including Kubernetes, MLflow, feature stores, model registries, and monitoring and observability tools.
Familiarity with generative AI patterns applied to healthcare, including LLMs, retrieval-augmented generation, and structured extraction or summarization, with evaluation approaches suitable for regulated environments.