GeBBS - Technical Architect - Data Science

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.

• 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.

(ref:hirist.tech)