Senior Algorithm Engineer- Wearable Medical Device

HealthCare Recruiters International; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

HealthCare Recruiters International is seeking a Senior Algorithms Engineer to develop and deploy time-series biomedical signal processing models for wearable health monitoring devices. The role emphasizes translating research into production-ready code and collaborating with hardware teams to optimize for low-power, real-time inference.

The candidate will lead biomarker discovery, feature extraction, and systematic validation in line with FDA-regulated processes, contributing to publications

Qualifications

• Masters (or PhD) in Biomedical/Electrical/Computer Engineering, Computer Science, or a related field.
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Responsibilities

• Design, build, validate, and optimize signal processing, machine learning and deep learning models for time-series biomedical signal analysis
• Lead biomarker discovery and feature engineering initiatives, including planning and managing short-term and long-term project timelines with deliverables and performance targets
• Collaborate with hardware and embedded teams to transition algorithms into low power implementations
• Document processes and results to comply with internal and FDA-regulated processes
• Contribute to research publications, IP development, and technical strategy

Skills

Biomedical signal processing

Machine learning

Time-series analysis

Algorithm development

Production-grade code

Education

Master's degree in Biomedical/Electrical/Computer Engineering, CS

PhD in Biomedical/Electrical/Computer Engineering, CS (optional)

Tools

Python

NumPy

SciPy

PyTorch

TensorFlow

scikit-learn

Swift

C/C++

LiteFlite

Job description

Our client is a well-funded innovator in the development and commercialization of wearable (non-invasive) health monitoring wearable platforms specifically for patients suffering from a range of cardiovascular and neurological disorders.

They have immediate need for a Senior Algorithms Engineer, with a strong background in biomedical signal processing, machine learning, or related field. This role is focused on interpreting time-series signals from wearable devices in both post-processing and real-time contexts for interpreting predictive physiologic data to provide relevant status to patients and physicians.

Key Responsibilities:

• Design, build, validate, and optimize signal processing, machine learning and deep learning models for time-series biomedical signal analysis
• Lead biomarker discovery and feature engineering initiatives, including planning and managing short-term and long-term project timelines with deliverables and performance targets
• Collaborate with hardware and embedded teams to transition algorithms into low power implementations
• Document processes and results to comply with internal and FDA-regulated processes
• Contribute to research publications, IP development, and technical strategy

Qualifications (required and/or preferred):

• Masters (or PhD) in Biomedical/Electrical/Computer Engineering, Computer Science, or a related field
• 3+ years relevant industry (beyond academic & research) experience in time-series biomedical signal analysis (e.g., EEG, ECG, PPG, EMG, IMU)
• Strong experience in machine learning, model development, statistical modeling, and signal processing techniques
• Fluent in Python, NumPy, SciPy, PyTorch/TensorFlow, scikit-learn
• Proven ability to write clean, efficient, production-quality code
• Experience translating research algorithms into deployable systems, including generation of required documentation and implementing traceability of testing/validation processes
• Experience in biomarker discovery and physiological feature extraction
• Experience optimizing algorithms to improve performance within constraints
• Familiarity with edge deployment frameworks including Swift, C/C++, LiteFlite, etc.