Software Engineer II - Diagnostics Research Team

Additional Location(s):  N/A

Diversity - Innovation - Caring - Global Collaboration - Winning Spirit - High Performance

At Boston Scientific, we’ll give you the opportunity to harness all that’s within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, we’ll help you in advancing your skills and career. Here, you’ll be supported in progressing – whatever your ambitions.           

 

About the role:

Boston Scientific’s Diagnostics Research Team (Cardiac Rhythm Management & Diagnostics) develops and evaluates new diagnostic and monitoring capabilities for cardiac devices—translating early research into validated prototypes and technologies that can be transferred into product development.

In this Software Engineer II role, you’ll build and support software used in research environments—bench test systems, data pipelines, databases, automation, and calibration workflows, develop AI/ML-based algorithms (e.g., dynamic calibration/compensation and signal-driven detection/prediction features) —working closely with cross-functional engineering and research partners.

 

Work model and sponsorship:

This role follows an onsite work model, requiring employees to be in our Arden Hills, MN office at least four days per week. Boston Scientific will not offer sponsorship or take over sponsorship of an employment visa for this position.  

 

Your responsibilities will include:

• Develop and maintain software for bench test systems, including instrumentation control, automation workflows, and data acquisition.
• Design and implement data systems: databases, data trend/analytics pipelines, and reliable interfaces to internal enterprise data platforms.
• Build calibration automation capabilities and integrate them into test and verification workflows.
• Develop AI/ML-based algorithms for classification, and/or prediction algorithms based on cardiac ECG and physiologic signals.
• Collaborate with scientists and engineers to design experiments/simulations, evaluate performance, and validate models/algorithms against ground truth and bench/clinical datasets where applicable.
• Produce clear engineering documentation (requirements, design notes, test plans, test reports, procedures) and contribute to technical reviews.
• Troubleshoot complex system issues across software, data, and test setups; propose robust fixes and preventive improvements.
• Contribute to intellectual property and innovation activities (e.g., invention disclosures, patent support) when novel solutions are developed.

 

Required qualifications:

• Bachelor’s degree in Computer Science, Software Engineering, Electrical Engineering, Biomedical Engineering, or a related engineering discipline.
• 2+ years of relevant work experience.
• Professional, co-op, or internship experience in software development (or equivalent project experience).
• Proficiency in Python (and/or comparable languages) and comfort working across data, automation, and engineering workflows.
• Familiarity with at least two of the following: test automation, database design/SQL, data pipelines, CI/CD, API development, instrumentation integration, or data visualization/trending.

• Experience with data science techniques (e.g., data mining, machine learning and/or deep learning models) 

• Strong communication and collaboration skills; ability to work effectively in a fast-paced, cross-functional R&D environment.

 

Preferred qualifications:

• Experience developing or applying machine learning methods (e.g., regression/classification, deep learning) for real-world data problems, including model evaluation and validation.
• Experience with dynamic calibration/compensation approaches or model-based calibration in sensor or measurement systems.
• Experience with time-series / physiologic signals (e.g., ECG or related biosignals), feature engineering, and algorithm validation.
• Proficiency in using LabVIEW for multiple instrumentation control
• Exposure to re