- Develop custom generative models using deep learning frameworks, training models on large-scale datasets with advanced optimization techniques, and fine-tuning parameters to optimize performance metrics.

Performance Evaluation and Optimization :

- Evaluate model performance using quantitative and qualitative metrics, identifying areas for improvement, and optimizing model architectures to ensure efficiency and effectiveness of generative AI solutions.

Integration and Deployment :

- Integrate generative AI models into existing systems and applications, developing APIs and interfaces for seamless interaction with other components, and ensuring compatibility, scalability, and reliability in production environments.

Collaboration and Communication :

- Collaborate with cross-functional teams to understand requirements, effectively communicate technical concepts to stakeholders, and provide guidance and mentorship to junior team members.

Technical Expertise :

- Should have worked hands-on in setting up ML services on public cloud and delivering ML based solutions.

- Should have 1 to 3 years of experience in AI, ML and at least 1 year in GenAI leveraging cloud based and other GenAI services.

- Should have working knowledge on deployment of GenAI solutions to customers cutting across the industry prevalence of GenAI.

- Should have hands-on experience in prompt engineering, maintaining prompt libraries, managing GenAI delivered code (filtering, avoiding duplicates etc.)

- Should have created PoVs or PoCs and presented to client teams.

- Working experience on Automation tools and platform would be advantage