Sr. Algorithm Engineer - Wearable Health & Sensor Algorithms

Gonoise

Gurugram District

On-site

INR 1,500,000 - 2,600,000

Full time

9 days ago

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Job summary

Gonoise in Gurugram, India (Onsite) seeks an experienced Algorithm Engineer to lead health and wellness algorithms for wearables. You will work across biosignal processing, sensor fusion, and embedded deployment on RTOS platforms, collaborating with hardware, firmware, data science, cloud, and product teams.

The role emphasizes design, validation, and performance benchmarks, with focus on HR, HRV, SpO2, Sleep, and related physiological metrics for next‑gen devices.

Qualifications

  • 5–7+ years in wearable health algorithms or biosignal analysis.
  • Experience with embedded platforms and medical/fitness sensing.
  • Strong background in DSP and sensor fusion.

Responsibilities

  • Design and optimize HR, HRV, SpO2, sleep, and wellness metrics for wearables.
  • Develop robust signal processing pipelines for PPG, ECG, IMU, and sensors.
  • Build multi-sensor fusion frameworks and validate against references.
  • Collaborate with hardware, firmware, data science, cloud, and product teams.
  • Lead calibration, validation, and performance benchmarking initiatives.

Skills

Biosignal processing
Sensor fusion
Embedded deployment
DSP
Python
MATLAB
C/C++
RTOS
Machine learning

Education

Bachelors in Biomedical Engineering
Master or PhD in related field
Signal Processing
Electrical Engineering

Tools

Python
MATLAB
C/C++

Job description

Role: Algorithm Engineer


Location: Gurugram, India (Onsite)


About the Role We are looking for a highly experienced Algorithm Engineer to lead the development of next-generation health and wellness algorithms for wearable devices including smartwatches, smart rings, and fitness trackers. The ideal candidate will have strong expertise in biosignal processing, sensor fusion, physiological modeling, and production-grade algorithm deployment on embedded wearable platforms. This role involves working closely with hardware, firmware, data science, cloud, and product teams to build industry-leading health monitoring experiences.


Key Responsibilities

Health Algorithm Development


  • Design, develop, and optimize algorithms for: Heart Rate (HR), Resting Heart Rate (RHR), Heart Rate Variability (HRV), Blood Oxygen -Saturation (SpO₂), Sleep Monitoring & Sleep Staging, Stress Monitoring, Respiratory Rate, Activity & Energy Expenditure Tracking, Recovery & Readiness Metrics, Women’s Health Tracking, Advanced Vital Sign Monitoring


Signal Processing


  • Develop robust signal processing pipelines for: PPG (Photoplethysmography), ECG, Accelerometer, Gyroscope, Temperature Sensors, Bioimpedance Sensors

  • Design motion artifact removal and noise suppression algorithms.

  • Improve signal quality under challenging real-world conditions.


Sensor Fusion


  • Build multi-sensor fusion frameworks combining optical, inertial, physiological, and environmental sensors.

  • Enhance accuracy and reliability across different use cases and user populations.


Validation & Calibration


  • Design calibration methodologies for wearable sensors.

  • Define validation protocols and benchmark performance against clinical-grade references.

  • Analyze large-scale datasets to improve algorithm accuracy and robustness.


Embedded Deployment


  • Optimize algorithms for low-power embedded systems.

  • Work with firmware teams to deploy algorithms on resource-constrained RTOS platforms.

  • Improve computational efficiency, memory utilization, and battery consumption.


Research & Innovation


  • Stay updated on advancements in digital health, biosignal processing, AI/ML, and wearable sensing technologies.

  • Drive innovation through prototyping, experimentation, publications, and patent generation.

  • Evaluate emerging sensing technologies and health metrics.


Cross-functional Leadership


  • Collaborate with Hardware, Optical Design, Firmware, Mobile App, Cloud, and Product teams.

  • Mentor junior engineers and establish best practices for algorithm development and validation.


Required Qualifications


  • Bachelors or Master's or PhD in:

  • 5–7+ years of experience in wearable health algorithms, biosignal processing, or physiological data analytics.

  • Biomedical Engineering

  • Signal Processing

  • Electrical Engineering

  • Computer Science

  • Applied Mathematics

  • Related disciplines


Technical Skills


  • Strong understanding of: Digital Signal Processing (DSP), Statistical Signal Analysis, Time-Series Analysis, Sensor Fusion, Physiological Signal Processing

  • Hands-on experience with:


    • PPG signal processing, Motion artifact reduction, HR and HRV estimation, Sleep algorithms, SpO₂ algorithms

    • Python, MATLAB, C/C++, Data analysis frameworks

    • Embedded deployment, RTOS-based systems, Low-power optimization

    • Machine Learning and Deep Learning for physiological data.



Good to Have


  • Clinical validation studies.

  • Regulatory exposure (FDA, CE, ISO 13485).

  • Patent filings and published research.

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