Deep Learning Scientist

Please share your resume to hr@webcardio.com

About this role

In this role, you will be part of a data rich, multidisciplinary team of AI scientists, ML Software

engineers, subject matter experts & annotators responsible for developing, validating, updating &

deploying cutting edge DL models on ECG data for various diagnostic & predictive problems related to arrhythmia & related issues. Examples include detection of AFIB and risk scores for Stroke related patient stratification.

Responsibilities

• Model Development: Design and implement advanced deep learning models specifically tailored for analyzing ECG data to identify arrhythmias and related cardiovascular conditions with very high accuracy. This includes models for beat detection, beat classification, rhythm classification, other risk scoring and predictive models.
• Data Processing: Collaborate with multidisciplinary teams to create targeted ECG datasets for various directed usecases, ensuring data quality and relevance for model training and validation.
• Validation, Testing & Monitoring: Develop robust methods to assess model performance and developing an understanding of failure modes, towards explainable AI and insights for continuous improvement of the models.
• Cross-Disciplinary Collaboration: Work closely with AI scientists, ML software engineers, and subject matter experts. Additionally, will engage in collaborative discussions with key opinion leaders in cardiology and their teams.
• Model Optimization: Continuously improve model architectures and algorithms based on feedback, new research findings, and emerging techniques in deep learning. This includes prototyping, testing & use of LLM & GEN-AI methods as appropriate.
• Deployment: Collaborate with engineering teams to deploy models in clinical settings, ensuring scalability, reliability, and compliance with relevant regulations.
• Documentation and Reporting: Maintain thorough documentation of model development processes, including methodologies, results, and insights for both technical and non-technical stakeholders.
• Research and Innovation: Stay updated on the latest advancements in deep learning, cardiovascular health, and related fields to drive innovative approaches to ECG data analysis.
• User Training and Support: Provide training and support to end-users and clinical staff on model functionality and interpretation of results to facilitate effective implementation in healthcare settings.
• Ethics and Compliance: Ensure adherence to ethical standards and compliance with regulatory guidelines throughout the model development and deployment process, particularly regarding patient data handling.

Skills Required

• Very comfortable with building & validating DL models, ML Ops and success in taking the models to production. High level of fluency in Python is expected.
• Expertise in Pytorch, Keras/Tensorflow, AWS services & GPUs.
• Strong command of the foundations of ML & DL, and aptitude for data science & analysis.
• Familiarity with multimodal LLM & GENAI developments
• Ability to work in a multidisciplinary environment with domain experts & software engineers.
• Strong communication skill is essential.
• Ability to quickly read research papers & implement novel models.
• Strong interest in working in AI for Healthcare.
• Experience working on models for sensor or time series data is preferred.
• Knowledge of ECG is preferred.

Qualifications:

• Bachelor's/Master's/PhD Engineering Degree in Computer science, Electrical Engineering,
• Biomedical engineering, Physics or related area

Experience (in years):

• 4+ years

Location: Kochi