Biomedical Systems Engineer – Connected MedTech

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.

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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

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

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

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

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)

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

1. Risk & Safety (Biomedical + System View)

• Identify:

• Physiological misinterpretation risks

• Sensor failure modes

• Contribute to:

• Risk analysis (ISO 14971)

• Clinical risk mitigation strategies

1. 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

Experience :

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

Experience in:

• 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 (Num Py, Pandas)

• Exposure to:

Embedded platforms (preferred)

• Data visualization tools

Preferred Skills :

Working knowledge of:

• ISO 13485

• ISO 14971

• Exposure to:

• Verification & Validation

• Design controls