(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.
- 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.




- 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).
- 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
- Robust 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.

📌 AI & Clinical Scientist (Vadodara)
🏢 Topia MedTech
📍 Vadodara