Roles and responsibilities
- Lead AI deployment activities, work with AI team to perform solution designing, architecting of automation solutions involving chatbots, AI
- Lead the chatbot solutions end to end delivery, continuously enhance the chatbot performance through data analytics.
- Be an active back-ups for one or more technologies within the team, drive innovation mindset
- Lead development efforts in Python, work closely with engineering team to deploy AI solutions in Docker, AKS containers.
- Create solution prototypes involving cloud infrastructure
- Build AI models in python, jupyter notebook, Watson or Azure machine learning platforms, chatbot frameworks, power automate, etc.
- Strong working knowledge in Deep Learning, Computer Vision libraries in python.
- Lead development efforts in Python, Java, create REST APIs in cloud and lead deployment of automation solutions.
Competencies and skills required
- Experience in developing AI/Machine learning solutions that are deployed in a production setting.
- Strong experience in NLP, experience in deploying solutions with BERT and Transformers in NLP.
- Strong python coding experience, experience in Azure Data Bricks and Azure platforms,
- Exoperience with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)
- Experience in Python based AI/Machine learning frameworks and toolchains such as Scikit learn, Keras, Tensorflow, Pytorch, Spacy and Anaconda.
- Experience with development environments and tools such as SQL, Git, Linux and Docker.
- Previous experience in deploying end-to-end AI/ML solutions will be advantageous.
- Understanding of cloud and on-premise infrastructure, experienced on Azure Cloud and Jboss server
- Good understanding of chatbot solutions either in Azure Framework, IBM Watson
- Good programming skills in the areas of Java, Javscript and SQL
- Good Understanding of insurance business processes
- Analytical & Innovation mindset