Company Overview :

Predigle is a rapidly growing technology company specializing in AI-powered solutions for the healthcare industry. We develop cutting-edge diagnostic tools and personalized treatment plans, leveraging machine learning to improve patient outcomes and streamline healthcare processes. Our solutions are deployed across leading hospitals and clinics, impacting thousands of lives daily.

Role Overview :

As an AI Engineer at Predigle, you will be at the forefront of developing and deploying innovative AI models to solve critical challenges in healthcare. You will collaborate closely with a team of data scientists, software engineers, and medical professionals to build, train, and optimize machine learning algorithms for medical image analysis, predictive diagnostics, and personalized medicine. Your work will directly contribute to improving the accuracy and efficiency of healthcare delivery, ultimately enhancing patient care.

Key Responsibilities :

- Design, develop, and deploy machine learning models for medical image analysis, predictive diagnostics, and personalized treatment plans to improve patient outcomes.

- Collaborate with data scientists to build and maintain robust data pipelines for training and evaluating AI models, ensuring data quality and integrity.

- Optimize model performance and scalability through techniques such as model compression, quantization, and distributed training to meet real-time performance requirements.

- Implement and maintain CI/CD pipelines for automated model deployment and monitoring, ensuring seamless integration with existing healthcare systems.

- Conduct research and stay up-to-date with the latest advancements in AI and machine learning to identify opportunities for innovation and improvement.

- Work closely with medical professionals to understand their needs and translate them into technical requirements, ensuring that AI solutions are aligned with clinical practice.

Required Skillset :

- Demonstrated ability to design, develop, and deploy machine learning models using Python and relevant libraries such as TensorFlow, PyTorch, and scikit-learn.

- Proven expertise in data preprocessing, feature engineering, and model evaluation techniques to ensure optimal model performance.

- Strong understanding of deep learning architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers.

- Experience with cloud computing platforms such as AWS, Azure, or GCP for deploying and scaling AI models.

- Excellent communication and collaboration skills to effectively work with cross-functional teams and stakeholders.

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.

- Ability to adapt to a fast-paced, dynamic environment and learn new technologies quickly.

- Minimum 5-8 years of experience in a similar role.