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. 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. (ref:hirist.tech) 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. (ref:hirist.tech)