Software Engineer II - Diagnostics Research Team
About The Position
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. 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 regulated product development practices (requirements, traceability, verification documentation) or medical device R&D environments. Master's degree in a related field.
Requirements
- 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.
- 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 regulated product development practices (requirements, traceability, verification documentation) or medical device R&D environments.
Nice To Haves
- Master's degree in a related field.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
