Source description
About the role
Bosch Global Software Technologies Private Limited is a 100% owned subsidiary of Robert Bosch GmbH, one of the world's leading global supplier of technology and services, offering end-to-end Engineering, IT and Business Solutions. With over 27,000+ associates, it’s the largest software development center of Bosch, outside Germany, indicating that it is the Technology Powerhouse of Bosch in India with a global footprint and presence in the US, Europe and the Asia Pacific region.
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
- 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
- Risk & Safety (Biomedical + System View) Identify: Physiological misinterpretation risks
Sensor failure modes
Contribute to: Risk analysis (ISO 14971)
Clinical risk mitigation strategies
- 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 (NumPy, Pandas)
Exposure to: Embedded platforms (preferred)
Data visualization tools
Preferred Skills :
Working knowledge of: ISO 13485
ISO 14971
Exposure to: Verification & Validation
Design controls
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