About the Role Uber AI Solutions is one of Uber’s biggest bets with the ambition to build one of the world’s largest data foundries for AI applications and evolve into a platform of choice for a variety of online tasks. The Moonshot AI team focuses on optimizing the Uber AI Solutions gig marketplace through intelligent supply and demand matching. We also accelerate human-in-the-loop data annotation and collection with automation and develop robust automated evaluation systems. We are in the early stages, with significant opportunities to conduct foundational and applied research in the GenAI space. This includes advanced ML models to enable human-in-the-loop data annotation with advanced automation, and develop novel automated evaluation systems. In this role, you will collaborate closely with product managers, program managers, and cross-functional teams to deliver real-world impact through your research. You’ll help grow Uber AI Solutions into a leader in the space. What the Candidate Will Do: Drive research in areas such as LLM post-training (RLHF, GRPO, instruction tuning), data efficiency, and the design of benchmarks to evaluate LLM capabilities across safety, reasoning, and domain-specific performance. Design and run experiments to validate hypotheses and iterate on research ideas. Collaborate with research scientists and engineers to prototype and evaluate novel approaches. Produce publication-ready research targeting top-tier AI/ML conferences. What the Candidate Will Need: A Ph.D. or Masters in Computer Science, Machine Learning, or a related field. 2+ years of post-PhD or 5+ years of post-Masters research experience in an academic or industrial setting. A strong publication record in top-tier AI/ML conferences and journals, demonstrating a history of impactful research. Deep expertise in at least one of the following areas: Computer Vision (CV), Natural Language Processing (NLP), or Deep Learning, with a strong grasp of modern Generative AI techniques (e.g., Transformers, Diffusion Models, LLMs). Bonus Points if Candidate Has : 5+ years of industry or academic research experience in ML/AI. Proven track record of training large models on distributed infrastructure for research purposes. Demonstrated ability to rapidly prototype and iterate on research ideas, signaling curiosity and an experimental approach. Experience collaborating effectively across an organization, not limited to just within teams, to drive research adoption.

About Uber

We are Uber. The go-getters. The kind of people who are relentless about our mission to help people go anywhere and get anything and earn their way. Movement is what we power. It’s our lifeblood. It runs through our veins. It’s what gets us out of bed each morning. It pushes us to constantly reimagine how we can move better. For you. For all the places you want to go. For all the things you want to get. For all the ways you want to earn. Across the entire world. In real time. At the incredible speed of now. The idea for Uber was born on a snowy night in Paris in 2008, and ever since then our DNA of reimagination and reinvention carries on. We’ve grown into a global platform powering flexible earnings and the movement of people and things in ever expanding ways. We’ve gone from connecting rides on 4 wheels to 2 wheels to 18-wheel freight deliveries. From takeout meals to daily essentials to prescription drugs to just about anything you need at any time and earning your way. From drivers with background checks to real-time verification, safety is a top priority every single day. At Uber, the pursuit of reimagination is never finished, never stops, and is always just beginning.