Back
Tier-1 brand, mid-level ML role and metro location create high candidate competition.
Core LLM, ML, Python and Langchain skills are highly transferable across industries.
Explicit 5+ years, LLM/GenAI, Langchain, Python and production readiness imply highly strict filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop and implement machine learning solutions focusing on large language models (LLMs) using Langchain framework, including fine-tuning and Retrieval-Augmented Generation (RAG) techniques.
Produce production-quality Python code adhering to PEP8 standards, with thorough testing, documentation, and use of containerization (Docker) for deployment.
Work with traditional ML methods like XGBoost and unsupervised learning (K-means), and perform development and deployment tasks on the terminal.
Graduate degree or equivalent experience.
Minimum 5 years of experience in traditional machine learning, deep learning, and generative AI.
Proficiency in Python programming with adherence to PEP8 standards and experience with version control (Git).
Experience with LLMs, Langchain framework, RAG methodologies, and basic containerization technologies such as Docker.
Experience applying fine-tuning and RAG techniques to optimize language models for specific NLP tasks.
Comfortable managing end-to-end ML workflows including production deployment and code maintenance in terminal environments.
Skilled in both advanced LLM frameworks (Langchain) and traditional ML techniques, indicating versatility and depth in ML engineering roles.