AI Support Engineer

Key Responsibilities
•    To troubleshoot and resolve tickets raised by the clients.
•    To document all the defined processes and the methods of resolving the ticket| troubleshooting| etc.
•    To interface with customers for ticket clarification/resolution
•    To update self on latest technologies and related areas
Hard skills
•    Programming knowledge, expertise of programming languages such as Python, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. 
•    Expertise in generative models such as generative adversarial networks (GANs) and variational autoencoders (VAEs)
•    Natural language processing (NLP) for text generation projects. 
•    This includes familiarity with techniques for text parsing, sentiment analysis, and the use of transformers like GPT (generative pre-trained transformer) models.
•    Data management knowledge, including data pre-processing, augmentation, and generation of synthetic data. This involves cleaning, labeling, and augmenting data to train and improve AI models.
•    Cloud computing and deployment knowledge for deploying and managing AI applications on cloud platforms like AWS, Google Cloud, or Microsoft Azure. This includes understanding containerization technologies like Docker and orchestration tools like Kubernetes, which are important for scaling AI solutions.
Soft skills
•    Problem solving for thinking outside the box to design and implement novel AI solutions when faced with unprecedented challenges.
•    Analytical thinking for assessing model performance, interpreting outcomes, and making data-driven decisions for model improvement.
•    Collaboration and communication for articulating technical details and project needs to technical and non-technical team members, including data scientists, software developers, and business stakeholders.
•    Continuous learning for keeping up the latest research, tools, and techniques in the rapidly evolving generative AI landscape