(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

- 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

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 robust 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