$130K - 180K a year
Design, fine-tune, deploy LLMs and RAG pipelines, develop generative AI solutions, optimize models, and deploy scalable AI systems on cloud platforms.
Proficiency in Python and NLP frameworks, strong knowledge of transformer models, experience with vector search databases, cloud AI platforms, containerization, and strong analytical skills.
We are hiring an AI Engineer specializing in LLMs (Large Language Models), Retrieval Augmented Generation (RAG), and Generative AI. The role involves building advanced AI solutions that leverage state-of-the-art technologies. Key Responsibilities • Design, fine-tune, and deploy LLMs using frameworks like Hugging Face or OpenAI APIs. • Build and implement RAG pipelines with vector databases (e.g., Pinecone, FAISS). • Develop Generative AI solutions, including chatbots, summarization, and content creation tools. • Preprocess, clean, and annotate datasets for training and evaluation. • Optimize models for performance using techniques like quantization and pruning. • Deploy scalable solutions in production using Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure). • Monitor and troubleshoot deployed models for accuracy and reliability. • Collaborate with cross-functional teams to align AI capabilities with business objectives. • Stay updated with advancements in AI/ML research and integrate best practices. Requirements • Proficiency in Python and NLP frameworks (Hugging Face, spaCy, PyTorch, TensorFlow). • Strong understanding of transformer architectures and generative models like GPT or BERT. • Experience with vector search databases (Pinecone, Weaviate, Elasticsearch). • Familiarity with cloud-based AI platforms and containerization tools. • Excellent problem-solving, analytical, and communication skills.
This job posting was last updated on 10/14/2025