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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: Marketplace Optimization: Building intelligent supply-demand matching and ranking models to optimize our global gig marketplace. Custom Model Development: Training custom models to automate critical annotation workflows for audio, video, and text data. Automated Quality Evaluation: Utilizing GenAI and LLM-as-Judge frameworks to execute automated, enterprise-scale quality evaluation. 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.
Job Responsibility
Shape the technical vision and roadmap for Moonshot AI's ML initiatives
Architect foundational ML platforms and systems for marketplace optimization and annotation automation
Drive end-to-end ML solutions from conception through production deployment
Lead GenAI innovation: design and implement cutting-edge systems using custom SLMs, computer vision, and LLMs
Advance AI research capabilities: establish research direction, design benchmarks, contribute to research and publications
Build industry-leading evaluation frameworks: architect LLM-as-Judge systems and automated quality assessment platforms
Provide technical leadership across Uber AI Solutions
Mentor and develop engineering talent
Enable cross-functional impact
Requirements
10+ years of industry experience developing and shipping production machine learning models
Ph.D., MS, or Bachelor's degree in Computer Science, Machine Learning, or a closely related discipline
Proven track record of technical leadership on large-scale ML initiatives with measurable business impact
Deep expertise across multiple areas: Computer Vision, Natural Language Processing, Deep Learning, and Generative AI
Strong proficiency with modern ML frameworks (PyTorch, TensorFlow, JAX) and programming languages
Extensive experience with distributed training infrastructure, large-scale model development, and ML platform design
Demonstrated ability to collaborate with product, engineering, and data science leadership on technical roadmaps and strategic priorities
Excellent problem-solving abilities with deep ML methodology expertise
Nice to have
Ph.D. in Computer Science, Machine Learning, Statistics, or related field with focus on ML research
12+ years of ML/AI experience with demonstrated technical leadership across multiple organizations or product areas
Publications at top-tier AI/ML conferences demonstrating research impact
Expert-level experience with LLM fine-tuning techniques, prompt engineering, RAG systems, and multi-task learning
Deep experience with ML platform engineering including model serving, feature stores, experiment platforms, and observability systems
Domain expertise in marketplace optimization, recommendation systems, multi-armed bandits, or anomaly detection
Experience shaping technical vision and roadmaps for ML organizations
Proven ability to mentor senior engineers and elevate technical standards across teams
Background driving dataset development, including data collection, processing, labeling pipelines, and quality frameworks