Senior Algorithm Engineer- Wearable Medical Device

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
Develop production-grade code for scalable product deployment
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.

Work arrangement
No