LLM Engineer

February 11

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Ultralytics

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Ultralytics is an AI-focused company that provides an intuitive platform known as Ultralytics HUB for creating, training, and deploying machine learning models. With user-friendly capabilities, it allows individuals from various sectors, including agriculture, healthcare, and manufacturing, to develop AI-powered solutions easily and efficiently. By utilizing the Ultralytics YOLO framework, the platform enhances capabilities in computer vision, enabling users to optimize processes and solve complex challenges across industries.

AI • Deep Learning • Data Science • YOLOv5 • YOLOv8

11 - 50 employees

🤖 Artificial Intelligence

🌾 Agriculture

📋 Description

• Play a pivotal role in advancing our LLM capabilities • Researching, fine-tuning, and deploying state-of-the-art LLMs • Developing APIs and tools to enable seamless integration of LLM functionalities • Optimizing model performance for scalability and efficiency • Collaborating with the team to create innovative AI-driven solutions • Implementing automated checks for data quality and pipeline reliability • Supporting the integration of LLMs with Ultralytics solutions and workflows • Building internal company tools leveraging LLM capabilities • Designing and deploying Retrieval-Augmented Generation (RAG) applications • Enhancing query enrichment, reranking, and search relevance systems • Ensuring compliance with SOC 2 and ISO standards • Engaging with the open-source community to promote adoption and gather feedback • Writing and maintaining technical documentation and guides • Staying at the forefront of LLM advancements and sharing insights with the team

🎯 Requirements

• 5+ years of experience with Python and AI/ML frameworks • Extensive experience working with LLMs and transformer architectures • Strong understanding of NLP concepts, tokenization, embeddings, and fine-tuning • Proven experience deploying LLMs in production environments • Expertise with APIs from Anthropic , OpenAI , Voyage , DeepSeek , and Gemini • Experience with building internal tools leveraging LLM functionalities • Hands-on experience designing and implementing RAG applications • Proficiency in query enrichment and reranking methodologies • Familiarity with SOC 2 and ISO compliance requirements • Strong debugging and optimization skills • Excellent written communication and documentation abilities • Familiarity with open-source AI tools and communities • Experience with Docker and cloud-based deployment AWS , GCP , or Azure

🏖️ Benefits

• 24 days paid vacation • your birthday off • plus local holidays. • Flexible working hours. • budget and measures to bring the entire team together on an occasional basis.