Role and Responsibilities :

- Solution Design : Architect the development of AI solutions from conceptualization to deployment.

- Leadership : Lead the development, deployment, and optimization of machine learning (ML), natural language processing (NLP) models, and LLM/GenAI solutions.

- Pipeline Development : Develop and maintain Python-based ML pipelines and manage associated databases.

- Model Deployment : Deploy AI models on Azure/AWS, ensuring optimal performance and scalability.

- Mentorship : Stay updated on advancements in ML, NLP, and GenAI, and mentor team members to enhance their skills and knowledge.

- Best Practices : Implement LLMOps best practices for efficient management of the model lifecycle.

Skillset Requirements :

- Experience : 8 to 11 years of relevant experience in data science.

- Programming : Minimum of 8 years of experience in Python programming.

- Machine Learning/NLP : At least 8 years of experience in machine learning and natural language processing.

- LLM and GenAI : A minimum of 2 years of experience with large language models (LLMs) and generative AI (GenAI).

- Agentic AI : A minimum of 1 year of experience with Agentic AI.

- Database Management : At least 8 years of experience with any database.

- Cloud Deployment : 4+ years of knowledge in deploying ML models/Python applications on Azure or AWS.

- LLMOps : Familiarity with LLMOps is mandatory.