Machine Learning Engineer (RAGs)

Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field 5+ years of hands-on experience developing and deploying machine learning models in production environments 4+ years of experience with production NLP and deep learning models using frameworks like PyTorch and TensorFlow 1+ year of experience with Retrieval-Augmented Generation (RAG) and other advanced techniques Proven experience writing production-level code, with strong proficiency in Python Expertise in working with large language models (LLMs) such as GPT, Gemini, and Claude Proficiency in LLM frameworks like LangChain Strong understanding of prompting techniques Experience with cloud platforms such as AWS or GCP (AWS preferred) Experience with equivalent on-premise platforms

Design, develop, and optimize Retrieval-Augmented Generation (RAG) models Improve RAG model performance through algorithms and techniques Collaborate with client Data and Engineering teams to build machine learning infrastructure Work with client leadership to identify AI/ML opportunities Fine-tune and adapt large language models (LLMs) for RAG Partner with cross-functional client teams to deploy RAG models into production Apply advanced machine learning techniques, including LLMs, to develop AI solutions Write clean, maintainable, and scalable code Prioritize user experience and customer needs Design and develop frameworks for GenAI products Build and implement machine learning models and algorithms Provide technical leadership in identifying and evaluating AI/ML opportunities