AI Engineer_ LLMOps (Pune)

Required Qualifications: - 3 - 5 years of experience in working on ML projects that includes business requirement gathering, model development, training, deployment at scale and monitoring model performance for production use cases - Robust knowledge on Python, NLP, Data Engineering, Langchain, Langtrace, Langfuse, RAGAS, AgentOps (optional) - Should have worked on proprietary and open-source large language models - Experience on LLM fine tuning, creating distilled model from hosted LLMs - Building data pipelines for model training - Experience on model performance tuning, RAG, guardrails, prompt engineering, evaluation, and observability - Experience in GenAI application deployment on cloud and on-premises at scale for production - Experience in creating CI/CD pipelines - Working knowledge on Kubernetes - Experience in minimum one cloud: AWS / GCP / Azure to deploy AI services - Experience in creating workable prototypes using Agentic AI frameworks like CrewAI, Taskweaver, AutoGen - Experience in light weight UI development using streamlit or chainlit (optional) - Desired experience on open-source tools for ML development, deployment, observability, and integration - Background on DevOps and MLOps will be a plus - Experience working on collaborative code versioning tools like GitHub/GitLab - Team player with good communication and presentation skills Required Qualifications: - 3 - 5 years of experience in working on ML projects that includes business requirement gathering, model development, training, deployment at scale and monitoring model performance for production use cases - Robust knowledge on Python, NLP, Data Engineering, Langchain, Langtrace, Langfuse, RAGAS, AgentOps (optional) - Should have worked on proprietary and open-source large language models - Experience on LLM fine tuning, creating distilled model from hosted LLMs - Building data pipelines for model training - Experience on model performance tuning, RAG, guardrails, prompt engineering, evaluation, and observability - Experience in GenAI application deployment on cloud and on-premises at scale for production - Experience in creating CI/CD pipelines - Working knowledge on Kubernetes - Experience in minimum one cloud: AWS / GCP / Azure to deploy AI services - Experience in creating workable prototypes using Agentic AI frameworks like CrewAI, Taskweaver, AutoGen - Experience in light weight UI development using streamlit or chainlit (optional) - Desired experience on open-source tools for ML development, deployment, observability, and integration - Background on DevOps and MLOps will be a plus - Experience working on collaborative code versioning tools like GitHub/GitLab - Team player with good communication and presentation skills