6-10 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
Strong 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
