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    Sr. Algorithm Engineer - Wearable Health & Sensor Algorithms

    Engineering Sr. Algorithm Engineer - Wearable Health & Sensor Algorithms Gurgaon Work Type: Full Time Apply Now, IndiaOn-SiteFull-time5–7 yrs experiencePosted 1mo ago
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    Job description

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

    Responsibilities:

    </strong><br><u>Health Algorithm Development</u><br>-<strong>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</strong><br><u>Signal Processing</u><br>-Develop robust signal processing pipelines for: PPG (Photoplethysmography), ECG, Accelerometer, Gyroscope, Temperature Sensors, Bioimpedance Sensors<br>-Design motion artifact removal and noise suppression algorithms.<br>-Improve signal quality under challenging real-world conditions.<br><u>Sensor Fusion</u><br>-Build multi-sensor fusion frameworks combining optical, inertial, physiological, and environmental sensors.<br>-Enhance accuracy and reliability across different use cases and user populations.<br><u>Validation & Calibration</u><br>-Design calibration methodologies for wearable sensors.<br>-Define validation protocols and benchmark performance against clinical-grade references.<br>-Analyze large-scale datasets to improve algorithm accuracy and robustness.<br><u>Embedded Deployment</u><br>-Optimize algorithms for low-power embedded systems.<br>-Work with firmware teams to deploy algorithms on resource-constrained RTOS platforms.<br>-Improve computational efficiency, memory utilization, and battery consumption.<br><u>Research & Innovation</u><br>-Stay updated on advancements in digital health, biosignal processing, AI/ML, and wearable sensing technologies.<br>-Drive innovation through prototyping, experimentation, publications, and patent generation.<br>-Evaluate emerging sensing technologies and health metrics.<br><u>Cross-functional Leadership</u><br>-Collaborate with Hardware, Optical Design, Firmware, Mobile App, Cloud, and Product teams.<br>-Mentor junior engineers and establish best practices for algorithm development and validation.</div><div><br><strong>Required

    Qualifications:

    </strong><br>

    • Bachelors or Master's or PhD in:</div><div>-<strong>5–7+</strong><strong> years of experience in wearable health algorithms, biosignal processing, or physiological data analytics.</strong></div><div>
    • Biomedical Engineering<br>
    • Signal Processing<br>
    • Electrical Engineering<br>
    • Computer Science<br>
    • Applied Mathematics<br>
    • Related disciplines</div><div><br><strong>Technical

    Skills:

    </strong><br><u>Must Have</u><br>

    • <strong>Strong understanding of: Digital Signal Processing (DSP), Statistical Signal Analysis, Time-Series Analysis, Sensor Fusion, Physiological Signal Processing</strong><br>
    • <u>Hands-on experience with:</u><br>
    • PPG signal processing, Motion artifact reduction, HR and HRV estimation, Sleep algorithms, SpO₂ algorithms<br>
    • Proficiency in:<strong> Python, MATLAB, C/C++, Data analysis frameworks</strong><br>
    • Experience with: Embedded deployment, RTOS-based systems, Low-power optimization<br>
    • Machine Learning and Deep Learning for physiological data.</div><div><br><u>Good to Have</u><br>
    • Clinical validation studies.<br>
    • Regulatory exposure (FDA, CE, ISO 13485).<br>
    • Patent filings and published research.</div>

    Job details are sourced from the employer's original posting.

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    Noise

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