Senior Algorithms Engineer

Analog Devices•Wilmington, MA

1d•$172,000 - $236,500•Onsite

About The Position

The demand for remote health monitoring and disease management will continue to grow exponentially as the continuum of care extends to remote settings. Next generation solutions enabling this transformation increasingly rely on providing actionable insights at the point of care - signal processing, data analytics, and AI/ML-enabled algorithms are core differentiators of these systems. The Digital Healthcare business group is seeking a hands-on and experienced Senior Algorithms Engineer to lead the design, development, and optimization of signal processing and data analytics algorithms for next-generation multi-parameter patient monitoring and diagnostic solutions. The ideal candidate has strong foundation in biomedical signal processing and data analytics with a proven record of developing algorithms for real-time or near–real-time systems. This role requires close collaboration with clinical, software, hardware, firmware and QA/RA teams to ensure algorithms are validated, reliable, and ready for production deployment.

Requirements

Bachelor’s degree in Electrical Engineering, Biomedical Engineering, Computer Engineering, Computer Science, or related field.
3–5+ years of experience in signal processing, real-time algorithms, or embedded medical device software.
Demonstrated expertise in physiological signal processing, including filtering, feature extraction/classification, and/or noise/artifact removal.
Strong proficiency in Python, C/C++, or similar languages used for modeling and embedded implementation.
Working knowledge of machine learning techniques applied to time-series or sensor data (e.g. regression, classification, anomaly detection).
Strong software development skills, including version control (Git) and basic software test methodologies.
Experience working under medical device software lifecycle processes (IEC 62304) and familiarity with ISO 13485 and ISO 14971.
Proven ability to validate algorithms using large datasets and statistical analysis techniques.
Strong communication skills with the ability to work across cross-functional hardware, firmware, clinical, and regulatory teams.

Nice To Haves

Master’s degree or Ph.D. in Biomedical Engineering, Electrical Engineering, Computer Science, Data Science, or related field.
Experience in designing classification, deep learning, or real-time physiological monitoring algorithms for optical (e.g. pulse oximetry), biopotential (e.g. ECG), and/or bioimpedance (e.g. EDA) vital signs monitoring (VSM) devices and applications.
Familiarity with wearable or ambulatory devices (Holter, patch monitors, chest straps).
A strong knowledge of systems physiology is a plus.
Experience optimizing algorithms for low-power or resource-constrained embedded systems.
Experience collaborating with external development partners or contract engineering teams.

Responsibilities

Algorithm Development & Data Analytics: Take ownership of the design, implementation, and optimization of algorithms, from concept through prototyping and performance evaluation.
Apply signal processing techniques to extract robust features from noisy, real-world sensor signals.
Explore and apply machine learning techniques to improve measurement accuracy, robustness, and reliability.
Combine classical signal processing and data-driven approaches where appropriate.
Analyze diverse datasets (clinical and device-generated) to ensure algorithm reliability across patient populations and physiological conditions.
Design Transfer: Implement algorithms in production-quality code (embedded C/C++, Python, or equivalent), ensuring reliability, eficiency, and maintainability.
Support Design Transfer of algorithms and software modules into production firmware and cloud-based systems.
Participate in software architecture decisions and ensure alignment with IEC 62304 development processes.
Cross-functional & Technical Collaboration: Serve as a primary technical contact for internal and external partners regarding algorithmic behavior, performance, and implementation constraints.
Collaborate closely with hardware, firmware, and clinical science teams to ensure full alignment between signal acquisition hardware and algorithm design.
Work with QA/RA and clinical teams to support documentation, traceability, and regulatory submissions.
Support, Debugging & Continuous Improvement: Support troubleshooting and root cause analysis of algorithmic or signal-quality issues observed in testing or manufacturing environments.
Collaborate with operations and test engineering teams to optimize production test algorithms and signal validation workflows.
Drive continuous improvement initiatives in algorithm robustness, noise immunity, and computational eficiency.