Data ScientistAI EngineerAI-ML Ops

Job Description:

• Design develop and deploy advanced machine learning and deep learning models to solve complex business and healthcare problems.

• Conduct exploratory data analysis (EDA) statistical analysis and hypothesis testing to uncover insights and validate business assumptions.

• Build scalable end-to-end ML solutions from data preparation and feature engineering to model deployment and monitoring.

• Develop and optimize NLP solutions using Transformer-based architectures (BERT GPT Hugging Face etc.) and representation learning techniques.

• Design and implement graph-based machine learning solutions using Graph Neural Networks (GNNs) where applicable.

• Build automate and maintain MLOps pipelines for model training validation deployment monitoring and lifecycle management.

• Deploy and manage machine learning models in cloud environments preferably on Azure using Azure Kubernetes Service (AKS) and CI/CD best practices.

• Develop robust data pipelines ETL processes and data integration workflows using modern data engineering practices.

• Work with large-scale high-dimensional datasets and optimize model performance scalability and reliability.

• Collaborate with cross-functional teams business stakeholders and global partners to translate business requirements into scalable AI and analytics solutions.

• Perform model monitoring drift detection observability and continuous improvement for production ML systems.

• Mentor junior team members and promote best practices in machine learning MLOps experimentation and software engineering.

• Stay updated with advancements in AI Machine Learning Generative AI MLOps and healthcare analytics.

Employment Type : Full Time
Experience: years
Vacancy: 1