LLM Engineer

Required skills

5+ years of experience in software engineering, with a strong focus on AI and Machine Learning (ML), Expert-level proficiency in Python and deep learning frameworks, particularly PyTorch, Proven experience building and deploying applications with LLM APIs such as OpenAI, Anthropic, Gemini, and DeepSeek, Hands-on experience with the full RAG pipeline, including vector embeddings, rerankers, and data indexing in databases like MongoDB, Practical knowledge of LLM fine-tuning, prompt engineering, and performance optimization, Familiarity with MLOps principles and tools, including CI/CD with GitHub Actions, A strong interest in computer vision and an understanding of object detection models like Ultralytics YOLO11

Preferred skills

Technologies

OpenAI, Anthropic, Gemini, LiteLLM, Voyage AI, MongoDB Atlas Vector Search, GitHub Actions, PyTorch, RAG, embeddings, rerankers, vector storage, CI/CD, LLM fine-tuning, prompt engineering, performance optimization, MLOps, computer vision, YOLO11

Responsibilities

Developing and scaling robust LLM-powered applications using a variety of APIs, Implementing and managing multi-API workflows using tools like LiteLLM to ensure flexibility and resilience, Building sophisticated Retrieval-Augmented Generation (RAG) systems, leveraging advanced techniques like embeddings with Voyage AI, rerankers, and query enrichment, Designing and maintaining efficient data pipelines and vector storage solutions using MongoDB Atlas Vector Search, Fine-tuning LLMs on custom datasets to enhance performance for specialized tasks related to our documentation and user support, Collaborating with our YOLO development team to explore and build innovative multi-modal solutions, Automating deployment and testing processes using CI/CD pipelines with GitHub Actions

Seniority

Domain

AI, Machine Learning, Computer Vision, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), MLOps, Software Engineering