Senior Staff Algorithm Engineer

External

Becton Dickinson · - Irvine Laguna Canyon, CA

Full-timeRemoteToday

ClusteringDocumentationElectronic Health RecordsFeature EngineeringForecastingMachine Learning

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About the role

We are seeking a highly experienced Senior Staff Algorithm Engineer with deep expertise in physiological signal processing, biomedical sensor data, and classical machine learning to help develop next-generation medical technologies for continuous patient monitoring, disease detection, and predictive clinical insights. In this role, you will design, develop, validate, and deploy algorithms that extract meaningful physiological parameters and clinical insights from complex, noisy, real-world sensor data. You will work with multi-modal data streams from monitoring sensors, bedside devices, wearable systems, electronic health records, and clinical datasets, with a primary focus on signal processing, statistical modeling, feature engineering, and interpretable machine learning approaches. This role is ideal for an experienced engineer who understands both the physics of sensing and the physiology behind the signals, and who can translate raw waveform data into reliable, clinically useful metrics for regulated medical technology products.

Responsibilities

Lead the design, development, validation, and deployment of algorithms for continuous physiological monitoring, new monitoring parameters and derived vital signs, signal quality assessment, artifact detection and rejection, multi-parameter trend analysis.

Develop robust algorithms using physiological waveform and sensor data.

Apply advanced signal processing techniques such as filtering and denoising, adaptive filtering, spectral analysis, time-frequency analysis, wavelet analysis, etc.

Build classical machine learning and statistical models for clinically relevant algorithm outputs, including, logistic regression, support vector machines, random forests, gradient boosting methods, probabilistic models, clustering and anomaly detection, time-series forecasting models.

Translate physiological and clinical understanding into meaningful algorithm features, performance requirements, model constraints, and interpretable outputs.

Develop end-to-end algorithm pipelines for data ingestion, synchronization, waveform preprocessing, segmentation, signal quality assessment, feature extraction, model training, validation, performance characterization, and robustness testing.

Work closely with clinical, systems engineering, software, embedded engineering, data science, regulatory, and quality teams to ensure algorithms are clinically meaningful, technically feasible, and suitable for regulated product development.

Optimize algorithms for edge and embedded medical devices with constraints on latency, memory, compute, battery life, and real-time performance, as well as for cloud-based platforms supporting scalable analytics and retrospective evaluation.

Support verification, validation, documentation, risk analysis, design controls, and clinical performance evaluation for regulated medical technology products.

Conduct root-cause analysis of algorithm performance issues using real-world clinical data and field data.

Contribute to intellectual property, technical strategy, algorithm roadmaps, scientific publications, and external technical engagement.

Mentor junior engineers and help establish best practices for physiological signal processing and algorithm development.

Minimum Required:

Bachelors degree in Electrical Engineering, Biomedical Engineering, Signal Processing, Computer Engineering, Applied Mathematics, Statistics, Physics, or a related quantitative or engineering discipline.

10+ years of industry experience in signal processing, algorithm development, biomedical engineering, medical devices, physiological monitoring, or related technical areas.

Deep expertise in digital signal processing and algorithm development for real-world sensor data.

Strong hands-on experience with physiological waveforms and biomedical signals such as ECG, PPG, respiration, blood pressure, capnography, or other patient monitoring signals.

Strong understanding of human physiology, particularly as it relates to cardiopulmonary function, hemodynamics, respiratory physiology, patient monitoring, and acute care.

Demonstrated experience developing algorithms from feasibility through productization, clinical validation, or deployment.

Experience designing robust signal processing pipelines for noisy, artifact-prone, real-world physiological data.

Strong background in feature engineering, statistical modeling, and classical machine learning.

Experience evaluating algorithm performance using clinically re

Senior Staff Algorithm Engineer

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