Senior Staff Machine Learning Engineer – Moonshot AI

Senior Staff Machine Learning Engineer – Moonshot AI Department: Engineering Team: Machine Learning Location: Sunnyvale, United States Type: Full-Time **About the role** The **Moonshot AI team** sits within Uber AI Solutions where we are building an enterprise AI data platform for leading AI labs and companies worldwide. We're a small, rapidly growing team tackling some of the most challenging problems in AI-assisted data annotation and validation, which means you'll have exceptional scope, ownership, and direct influence over both technical direction and business outcomes. In this role, your focus will be on delivering machine learning solutions across four core areas: 1. **Marketplace Optimization:** Building intelligent supply-demand matching and ranking models to optimize our global gig marketplace. 2. **Custom Model Development:** Training custom models to automate critical annotation workflows for audio, video, and text data. 3. **Automated Quality Evaluation:** Utilizing GenAI and LLM-as-Judge frameworks to execute automated, enterprise-scale quality evaluation. 4. **ML Research:** Publish robust benchmarks designed to identify loss patterns within SOTA models. You'll own projects end-to-end, from research and prototyping through production deployment, and your work will directly impact revenue growth, customer acquisition, and our competitive positioning. You'll collaborate with product managers, engineers, and cross-functional partners, in a fast paced startup-like environment. **What You'll Do:** - **Shape the technical vision and roadmap** for Moonshot AI's ML initiatives, identifying strategic investments that advance both technical excellence and business objectives - **Architect foundational ML platforms and systems** for marketplace optimization and annotation automation—designing scalable, reliable solutions that serve as the technical foundation for multiple product areas - **Drive end-to-end ML solutions** from conception through production deployment, owning critical technical decisions on architecture, tooling, and infrastructure that impact millions of tasks and revenue growth - **Lead G