Biomedical Systems Engineer - Connected MedTech

Requirements

• 12-17 years embedded systems development, preferably with medical or regulated devices.
• 5-10 years in:
• Biomedical engineering / medical devices / sensing systems
• Experience in:
• Sensor validation
• Experimental/bench testing
• Exposure to cross-functional development (HW + SW teams)
• Mandatory/requires Skills :
• Biomedical Core
• Strong understanding of:
• Human physiology (any domain)
• Physiological signal characteristics
• Biomedical instrumentation
• Sensor-based measurement systems
• Engineering Capability
• Sensor fundamentals (MEMS, optical, electrochemical basics)
• Signal acquisition concepts:
• ADC, sampling, noise
• Basic fluid/biophysical modeling (nice to have)
• Software & Data Awareness
• Programming:
• Python / MATLAB for data analysis
• Signal processing:
• Filtering, calibration, time-series analysis
• Basic understanding of:
• Embedded systems (MCU, interfaces)
• Data flow (BLE/Wi-Fi pipelines)
• Tools & Exposure
• Lab tools:
• DAQ systems, oscilloscopes, sensors
• Software:
• MATLAB / Python (NumPy, Pandas)
• Exposure to:
• Embedded platforms (preferred)
• Data visualization tools
• Preferred Skills :
• Working knowledge of:
• ISO 13485
• ISO 14971
• Verification & Validation
• Design controls

Additional Information

Roles & Responsibilities : The Biomedical Systems Engineer is responsible for defining, developing, and validating physiological sensing solutions for connected medical devices, ensuring accurate translation of biological signals into reliable engineering outputs . This role combines biomedical domain expertise with strong system, embedded, and data-oriented engineering capabilities , enabling development of scalable sensing solutions across a range of medical devices including diagnostic, therapeutic, and monitoring systems . The engineer will work across the lifecycle from physiological understanding ? sensor integration ? signal processing ? system validation , ensuring clinical relevance and engineering robustness. ? Key Responsibilities 1. Physiological Understanding & Signal Definition (Core Biomedical Anchor) Analyze physiological systems and identify clinically relevant measurable parameters Define: Pressure, flow, temperature Bio-signals (optional: ECG, SpO?, etc.) Map biological phenomena ? measurable electrical/physical signals Ensure clinical validity of measured parameters 2. Sensor Selection & Biomedical Validation Evaluate sensing technologies: MEMS, optical, thermal, electrochemical Define: Measurement range, sensitivity, response time Interaction with biological environments (fluids, tissues) Assess: Bio-compatibility considerations (early-stage) Impact of biological variability on signals 3. Signal Acquisition & Engineering Interface Work with electronics/embedded teams to define: Sensor interface requirements (AFE, ADC, sampling) Signal quality needs (noise, resolution) Support: Sensor integration into device architecture Selection of acquisition strategies 4. Signal Processing & Data Interpretation Develop and validate: Filtering and smoothing techniques Calibration and compensation models Convert raw data into: Clinically meaningful metrics Derived indicators (trend, anomaly, thresholds) Support implementation in: Embedded firmware or application layer 5. System Integration & Data Flow Understanding Define and validate end-to-end signal chain : Sensor ? Embedded ? Connectivity ? Application Work with: Embedded engineers (data acquisition) Mobile/cloud teams (data visualization & storage) Contribute to: Data formats (time-series, metadata) Interface/API definitions (basic level) 6. Experimental Design & Biomedical Validation Design and execute: Bench experiments Simulated physiological conditions Define: Test protocols Acceptance criteria Perform: Correlation with reference methods Repeatability and reliability analysis 7. Risk & Safety (Biomedical + System View) Identify: Physiological misinterpretation risks Sensor failure modes Contribute to: Risk analysis (ISO 14971) Clinical risk mitigation strategies 8. Platform Re-usability Develop reusable frameworks for: Physiological signal modeling Sensor validation Calibration approaches Enable reuse across: Patient monitoring systems Wearables Therapeutic devices Diagnostic platforms Educational qualification: B.E / B.Tech in Biomedical Engineering / ECE / EEE

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