Experience

8 to 11 Years

Job Description

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 productive management of the model lifecycle.

Skillset Requirements:

- Experience:



8-11 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.

📌 Technical Architect DataScience (Coimbatore)
🏢 ManpowerGroup
📍 Coimbatore