R&D Engineer (Medical Devices & Data Systems)

RESPIREE PTE. LTD.; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

RESPIREE PTE. LTD. is seeking a highly motivated R&D Engineer to join our Product Research team in Singapore.

The role focuses on designing and executing experimental studies, developing data processing and algorithmic solutions, and advancing next-generation medical technologies. You will operate at the intersection of physiology, signal processing, and system design, supporting data acquisition through analytical insight and product integration across disciplines.

Qualifications

• Strong proficiency in Python for data analysis and algorithm development.
• Experience with signal processing and time-series data.
• Familiarity with NumPy, SciPy, and Pandas libraries.
• Understanding of statistical methods and experimental design.

Responsibilities

• Design and execute internal clinical and non-clinical studies.
• Develop data processing pipelines and validation frameworks.
• Support integration of hardware, firmware, and software components.
• Investigate anomalies and translate findings into engineering solutions.

Skills

Python for data analysis

Signal processing

Time-series data

Statistical methods

Experimental design

Education

Bachelor's, Master’s, or PhD in Biomedical Engineering or Electrical Engineering

Tools

NumPy

SciPy

Pandas

Job description

We are seeking a highly motivated R&D Engineer to join our Product Research team. This role is responsible for designing and executing experimental studies, developing data processing and algorithmic solutions, and contributing to the development of next-generation medical technologies.

The successful candidate will work at the intersection of physiology, signal processing, and system design, supporting the full life cycle from data acquisition to analytical insight and product integration.

Key Responsibilities

Experimental Design & Validation

• Design and execute internal clinical and non-clinical studies
• Develop test protocols, data collection methodologies, and validation frameworks
• Ensure data quality, reproducibility, and adherence to relevant standards

Data Analysis & Algorithm Development

• Develop and maintain data processing pipelines using Python
• Implement signal processing, statistical, and machine learning algorithms
• Analyze physiological data to extract meaningful features and insights
• Evaluate performance across varying conditions and edge cases

System Development & Integration

• Contribute to the design of sensing and data acquisition systems
• Support integration of hardware, firmware, and software components
• Develop internal tools to support experimentation and analysis workflows

Research & Investigation

• Investigate anomalies, signal artifacts, and unexpected results
• Conduct literature reviews and apply cross-domain knowledge
• Translate research findings into practical engineering solutions

Education

• Bachelor’s, Master’s, or PhD in Biomedical Engineering, Electrical Engineering, Computer Science, or a related field

Technical Skills

• Strong proficiency in Python for data analysis and algorithm development
• Experience with signal processing and time-series data
• Familiarity with scientific computing libraries (e.g., NumPy, SciPy, Pandas)
• Understanding of statistical methods and experimental design

Experience

• Experience in R&D, product development, or applied research
• Exposure to biomedical signals (e.g., PPG, ECG, respiratory signals) is advantageous
• Familiarity with clinical studies or validation processes is a plus
• Experience with sensors, embedded systems, or hardware integration is beneficial

Core Competencies

• Strong analytical and problem-solving skills
• Ability to design structured experiments and interpret results rigorously
• Systems thinking with attention to detail
• Intellectual curiosity and a proactive approach to learning
• Ability to work independently and collaboratively in a multidisciplinary team

What We Offer

• Opportunity to work on cutting-edge medical technologies
• Direct impact on product innovation and patient outcomes
• Collaborative and research-driven work environment
• Exposure to interdisciplinary challenges across hardware, software, and data science