Experience: 3+ Years

Function: Medical Device R&D; / Signal Processing

Role Overview

We are looking for a Biomedical Signal Processing Engineer with hands-on experience developing and validating algorithms for physiological signals such as ECG, oscillometric BP/NIBP, PPG and SpO₂.

The role involves working with real sensor data, developing reliable signal-processing pipelines, improving algorithm performance, and supporting implementation in medical-device systems.

Key Responsibilities

- Develop signal-processing and measurement algorithms for ECG, NIBP/BP, PPG and SpO₂.
- Design, develop and optimize end-to-end physiological signal-processing pipelines, from raw signal acquisition through preprocessing, feature extraction and parameter estimation.
- Implement preprocessing methods including filtering, baseline removal, noise suppression and artifact reduction.
- Develop physiological feature-extraction methods such as:
- ECG QRS/R-peak detection and heart-rate calculation
- PPG pulse detection and waveform analysis
- Oscillometric pulse extraction, envelope generation, MAP, systolic and diastolic BP estimation
- Develop methods for detecting poor-quality or invalid signals.
- Analyze algorithm failures caused by motion, sensor contact, electrical interference, signal saturation and physiological variability.
- Optimize algorithm parameters and improve robustness across different users, devices and measurement conditions.
- Validate algorithm outputs against reference devices, datasets or annotated measurements using appropriate statistical/error metrics.
- Work with embedded and hardware engineers to integrate algorithms into real-time medical-device systems.
- Maintain algorithm documentation, test datasets, validation results and version history.
- Review relevant research and adapt suitable signal-processing methods for product development.

Required Skills

- Strong fundamentals in digital signal processing.
- Practical experience with physiological signals, preferably ECG and NIBP/BP.
- Knowledge of:
- FIR/IIR filtering




- FFT and frequency-domain analysis
- Peak detection
- Feature extraction
- Noise and artifact reduction
- Signal-quality assessment
- Solid proficiency in Python, including NumPy, SciPy, Pandas and Matplotlib.
- MATLAB experience is desirable.
- Basic/working knowledge of C/C++ for embedded implementation is preferred.
- Understanding of ECG morphology, PPG waveforms and oscillometric BP measurement principles.

Biomedical / Physiological Knowledge The candidate should have practical understanding of:

- ECG waveform morphology and QRS complexes
- Heart-rate and RR-interval measurement
- PPG waveform characteristics
- Principles of pulse oximetry
- Blood-pressure physiology
- Systolic, diastolic and mean arterial pressure
- Oscillometric NIBP measurement principles
- Common physiological and measurement artifacts

Deep clinical expertise is not mandatory, but the candidate should understand the physiological meaning of the signals being processed and how algorithm output relates to actual vital-sign measurements.

Qualification

B.E./B.Tech or M.E./M.Tech in:

- Biomedical Engineering
- Biomedical Instrumentation
- Electronics / ECE
- Electrical / EEE
- Instrumentation
- Signal Processing

or a related discipline with relevant biomedical signal-processing experience.

Experience

- 3+ years of relevant industry experience in biomedical signal processing, physiological signal analysis or medical-device algorithm development.
- Experience working with real acquired physiological data, including noisy and imperfect recordings.
- Demonstrated experience developing, testing, optimizing and validating signal-processing algorithms and processing pipelines.

Preferred

- Medical-device or patient-monitoring product experience.
- Experience with ECG, NIBP/BP and PPG/SpO₂ systems.
- Embedded/real-time algorithm implementation exposure.
- Experience in testing and validating biomedical algorithms against reference devices, annotated datasets, or ground-truth measurements, with quantitative performance analysis.
- Familiarity with IEC 62304, ISO 13485 or related medical-device development practices.

Work Location: In person

📌 Biomedical Signal Processing Engineer (Bengaluru)
🏢 Archle Labs
📍 Bengaluru