Technical Architect-Data Science

Department : Software Location: Coimbatore Work Mode: Work from Office Office Time: 11:00 AM 8:00 PM 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: 5-11 years of relevant experience in data science. Programming: Minimum of 5-8 years of experience in Python programming. Machine Learning/NLP: At least 4-8 years of experience in machine learning and natural language processing. LLM and GenAI: A minimum of 1-2 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 2 -8 years of experience with any database. Cloud Deployment: 1 -4+ years of knowledge in deploying ML models/Python applications on Azure or AWS. LLMOps: Familiarity with LLMOps is mandatory. Department : Software Location: Coimbatore Work Mode: Work from Office Office Time: 11:00 AM 8:00 PM 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: 5-11 years of relevant experience in data science. Programming: Minimum of 5-8 years of experience in Python programming. Machine Learning/NLP: At least 4-8 years of experience in machine learning and natural language processing. LLM and GenAI: A minimum of 1-2 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 2 -8 years of experience with any database. Cloud Deployment: 1 -4+ years of knowledge in deploying ML models/Python applications on Azure or AWS. LLMOps: Familiarity with LLMOps is mandatory.