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:

1. 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.
2. Design and run experiments to validate hypotheses and iterate on research ideas.
3. Collaborate with research scientists and engineers to prototype and evaluate novel approaches.
4. Produce publication-ready research targeting top-tier AI/ML conferences.

What the Candidate Will Need:

1. A Ph.D. or Masters in Computer Science, Machine Learning, or a related field.
2. 2+ years of post-PhD or 5+ years of post-Masters research experience in an academic or industrial setting.
3. A strong publication record in top-tier AI/ML conferences and journals, demonstrating a history of impactful research.
4. 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:

1. 5+ years of industry or academic research experience in ML/AI.
2. Proven track record of training large models on distributed infrastructure for research purposes.
3. Demonstrated ability to rapidly prototype and iterate on research ideas, signaling curiosity and an experimental approach.
4. Experience collaborating effectively across an organization, not limited to just within teams, to drive research adoption.

Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuelds progress. What moves us, moves the world - let's move it forward, together.

Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to accommodations@uber.com.