Sr Applied Scientist

Our mission is to make Uber the industry model for consumer privacy through differentiated, highly scalable, and extensible products and services, engineering standards, policy, and open communications. We are focusing on building both a privacy technology platform and user-facing products that give our users more control over their data, build trust, advance data privacy, and enable our business.

As a Sr Applied Scientist, you will lead efforts to develop and evaluate large-scale traditional machine learning models, optimize retrieval-augmented generation (RAG) systems, fine-tune large language models (LLMs), and implement agentic workflows. This role requires a strong foundation in both traditional machine learning and advanced LLM technologies.

Key responsibilities include:

• Developing and evaluating large-scale machine learning models in production
• Proposing, designing, and analyzing large scale online experiments
• Defining and implementing metrics to measure product performance
• Presenting findings to business and executive audiences
• Collaborating with engineers and product managers on implementation and roadmaps
• Optimizing RAG systems and fine-tuning LLMs
• Implementing agentic workflows

We're looking for candidates with a strong quantitative background, hands-on experience in ML model building and deployment, and proficiency in technologies like Python, R, SQL, Spark, and Hadoop. Experience with privacy and recommender systems, synthetic data generation, and advanced LLM technologies is highly valued.

Join our team to work on cutting-edge AI technologies while contributing to Uber's mission of enhancing user privacy and trust. You'll have the opportunity to work with large-scale data sets and apply your expertise in a dynamic, collaborative environment.