Job Opportunities API

About Ultralytics: At Ultralytics https://ultralytics.com/, we commit to relentless innovation in the AI space and seek team members https://www.ultralytics.com/about who resonate with our ambition to produce the world's best YOLO AI models https://ultralytics.com/yolo. If you're obsessed with AI, eager to make an impact on the world, and thrive in dynamic, high-intensity environments, we invite you to apply for a position on our team. 🌎 Where and how you can work This full-time LLM Engineer position is based at our brand-new Ultralytics office https://www.ultralytics.com/about in London, UK, with a hybrid model of three days in-office and two days remote. Applicants must have legal authorization to work in the UK, as Ultralytics does not provide visa sponsorship. 🚀 What you'll do As an LLM Engineer at Ultralytics, you will spearhead the development and integration of advanced language model capabilities across our ecosystem. You will work on cutting-edge projects that merge the power of large language models (LLMs) https://www.ultralytics.com/glossary/large-language-model-llm with our state-of-the-art computer vision https://www.ultralytics.com/glossary/computer-vision-cv technologies. Key responsibilities include: - Developing and scaling robust LLM-powered applications using a variety of APIs, including OpenAI https://developers.openai.com/api/docs/quickstart, Anthropic https://www.anthropic.com/claude, and Gemini https://deepmind.google/models/gemini/. - Implementing and managing multi-API workflows using tools like LiteLLM https://www.litellm.ai/ to ensure flexibility and resilience. - Building sophisticated Retrieval-Augmented Generation (RAG) https://www.ultralytics.com/glossary/retrieval-augmented-generation-rag systems, leveraging advanced techniques like embeddings with Voyage AI https://www.voyageai.com/, rerankers, and query enrichment. - Designing and maintaining efficient data pipelines and vector storage solutions using MongoDB https://www.mongodb.com/products/platform/atlas-vector-search Atlas Vector Search. - Fine-tuning LLMs on custom datasets to enhance performance for specialized tasks related to our documentation https://docs.ultralytics.com/ and user support. - Collaborating with our YOLO https://docs.ultralytics.com/models/yolo26/ development team to explore and build innovative multimodal solutions https://www.ultralytics.com/glossary/multi-modal-model. - Automating deployment and testing processes using CI/CD pipelines https://www.ultralytics.com/glossary/continuous-integration-ci with GitHub Actions https://github.com/features/actions. Your work will directly enhance the Ultralytics Platform https://docs.ultralytics.com/platform/ and empower our global community of developers and researchers. 🧠 Skills and experience - 5+ years of experience in software engineering, with a strong focus on AI and machine learning (ML) https://www.ultralytics.com/glossary/machine-learning-ml. - Expert-level proficiency in Python https://www.python.org/ and deep learning frameworks, particularly PyTorch https://pytorch.org/. - 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 https://www.mongodb.com/. - Practical knowledge of LLM fine-tuning https://www.ultralytics.com/glossary/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 https://www.ultralytics.com/blog/all-you-need-to-know-about-computer-vision-tasks and an understanding of object detection models like Ultralytics YOLO26 https://docs.ultralytics.com/models/yolo26/ is a significant plus. - Excellent problem-solving skills and the ability to perform in a fast-paced, high-intensity environmen