Uber - San Francisco, CA
posted 3 months ago
The Applied AI team at Uber is at the forefront of developing innovative AI solutions that address core business challenges. This team collaborates closely with various product teams to identify and understand these challenges, exploring the potential of AI to provide effective solutions. The focus areas of expertise within the team include Computer Vision, ML Optimization, Geospatial AI, Personalization, and Generative AI. Within this framework, the Generative AI team is dedicated to creating a semantic layer that enhances our comprehension of entities pertinent to the Uber platform, such as places, merchants, items, riders, and eaters. This involves working in partnership with other teams to design, develop, and productionize semantic data, features, and embeddings that align with business requirements. The role is pivotal in ensuring that AI solutions are not only innovative but also practical and applicable to real-world scenarios. As a Machine Learning Engineer in this team, you will be responsible for building and iterating on methods to capture semantic information related to Uber entities by utilizing Large Language Models (LLMs). You will generate embeddings from this semantic information, which will play a crucial role in enhancing our understanding of various entities, ultimately leading to improved machine learning models across Uber. Additionally, your work will contribute to the development of novel personalized experiences for users, leveraging the insights gained from the semantic data.