AI & Clinical Scientist

(JD)

Position: AI & Clinical Scientist – Cardiac Intelligence Platform

Department: Design & Development

Reporting To: Manager – Debanjan Parbat

Location: India (Hybrid)

Position Summary

The AI & Clinical Scientist – Cardiac Intelligence Platform will be responsible for developing, validating, and continuously improving AI-powered ECG analytics for the FibriArt ecosystem. The role combines expertise in Python-based AI development, ECG signal processing, clinical validation, and AI deployment to deliver clinically reliable, regulatory-compliant cardiac intelligence solutions.

The candidate will work closely with cardiologists, software developers, embedded engineers, regulatory teams, and product managers to build end-to-end AI solutions from data acquisition through clinical deployment.

Key Responsibilities

1. AI & Algorithm Development

• Develop AI/ML and deep learning models for ECG analysis, arrhythmia detection, signal quality assessment, and cardiac risk prediction.
• Design and optimize ECG preprocessing, filtering, feature extraction, and waveform analysis algorithms.
• Train, validate, and fine-tune AI models using Python-based frameworks.
• Improve AI performance through continuous model evaluation and optimization.

2. ECG Data & Clinical Validation

• Prepare, annotate, and validate ECG datasets for AI model development.
• Review ECG waveforms, arrhythmia labels, and signal quality with clinical experts.
• Benchmark AI models against cardiologist interpretations and public ECG databases (PTB-XL, MIT-BIH, PhysioNet, IRIDIA).
• Perform statistical validation using Sensitivity, Specificity, Accuracy, ROC/AUC, F1 Score, and Confusion Matrix.

3. AI Deployment & Platform Development

• Develop and maintain AI inference services using Python.
• Deploy AI models on cloud, web, and mobile platforms.
• Build APIs for integration with FibriArt mobile applications, dashboards, and backend systems.
• Monitor deployed models for performance, latency, drift, and reliability.

4. Clinical Research & Regulatory Support

• Support clinical validation studies and AI performance evaluations.
• Prepare technical documentation, validation reports, and AI performance summaries.
• Contribute to compliance activities aligned with FDA SaMD guidance, IEC 62304, ISO 14971, IEC 60601-2-47, and Good Machine Learning Practices (GMLP).

5. Cross-Functional Collaboration

• Work with embedded, software, biomedical, regulatory, QA, and clinical teams throughout product development.
• Coordinate with cardiologists and clinical investigators for AI validation and product improvement.
• Support product releases through verification, validation, and post-market AI performance monitoring.

Qualifications

• B.Tech/M.Tech in Computer Science, Artificial Intelligence, Biomedical Engineering, Electronics, Data Science, or related field.
• Ph.D/M.Sc. Cardiac Technology or Biomedical Signal Processing is an advantage.
• Ph.D or 2–6 years of experience in AI/ML, ECG analytics, biomedical signal processing, healthcare AI, or Software as a Medical Device (SaMD).

Required Technical Skills

Programming

• Python (Advanced)
• Object-Oriented Programming
• REST API development
• SQL/MySQL
• Git version control

AI & Machine Learning

• Scikit-learn
• TensorFlow or PyTorch
• Deep Learning (CNN, LSTM, Transformers)
• Time-series analysis
• Model optimization and hyperparameter tuning

ECG & Signal Processing

• ECG waveform interpretation
• Arrhythmia recognition
• Digital signal processing
• ECG preprocessing and filtering
• Feature extraction
• Noise and motion artifact reduction

Data & Cloud

• Pandas, NumPy, Matplotlib
• FastAPI or Flask
• Docker
• Linux
• Cloud deployment (AWS/Azure/GCP preferred)
• Basic MLOps concepts

Clinical & Regulatory Knowledge

• ECG annotation and validation
• AI performance evaluation metrics
• Clinical data analysis
• FDA AI/ML SaMD guidance (preferred)
• IEC 62304 and ISO 14971 awareness

Soft Skills

• Strong analytical and problem-solving abilities
• Clinical reasoning and scientific thinking
• Excellent documentation and communication skills
• Ability to work independently and in multidisciplinary teams
• Strong ownership and continuous learning mindset

Travel

• 10–30% travel for hospital collaborations, clinical studies, validation activities, and technical meetings.

Ideal Candidate

A self-driven engineer with strong expertise in Python, AI/ML, ECG signal processing, and clinical validation, capable of developing end-to-end cardiac intelligence solutions and translating clinical requirements into robust AI-enabled medical device software.