Machine Learning Engineer in EUROPEAN UNION

About the Company

Our client is an innovative real estate company committed to enhancing the way people interact with the real estate market. Their mission is to leverage cutting-edge technology to provide exceptional user experiences. They are building a state-of-the-art large language model (LLM) function for their website to revolutionize customer interactions and simplify property searches.

Role Overview

The client is seeking a highly skilled Machine Learning Engineer to develop, implement, and optimize a large language model for their platform. The role involves creating intelligent, user-focused solutions that transform the Real Estate experience. This position is fully remote, requiring availability during EU business hours.

Key Responsibilities

• Design, develop, and deploy LLM-based features tailored to the client's real estate platform.
• Implement Retrieval-Augmented Generation (RAG) techniques to enhance LLM performance and relevance.
• Fine-tune pre-trained models (e.g., GPT, Llama, etc.) to meet specific business and user needs.
• Integrate LLM capabilities into the client's website to enable natural language search, chatbot functionality, and personalized property recommendations.
• Collaborate with front-end and back-end development teams to ensure seamless integration of AI-powered solutions.
• Optimize model performance for speed, accuracy, and cost-efficiency.
• Conduct thorough testing and validation to ensure reliability and scalability.
• Stay informed of the latest advancements in machine learning and natural language processing.

Key Skills & Qualifications

• Proven experience in developing and deploying machine learning and NLP models, particularly large language models.
• Strong expertise in Python and ML frameworks/libraries such as TensorFlow, PyTorch, or Hugging Face Transformers.
• Hands-on experience with fine-tuning pre-trained LLMs for specific applications.
• Knowledge of Retrieval-Augmented Generation (RAG) and its implementation.
• Familiarity with APIs and integration of AI solutions into web applications.
• Experience with cloud platforms such as AWS, Google Cloud, or Azure for deploying ML models.
• Strong analytical and problem-solving skills with a results-driven approach.
• Excellent communication and collaboration skills, especially in remote team environments.