Senior Staff Machine Learning Engineer – Moonshot AI

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 GenAI innovation: design and implement cutting-edge systems using custom SLMs, computer vision, and LLMs to provide ML assistance for annotations across audio, video, and text workflows while establishing quality standards
• Advance AI research capabilities: establish research direction, design benchmarks, contribute to research and publications that positions Uber AI Solutions as a thought leader
• Build industry-leading evaluation frameworks: architect LLM-as-Judge systems and automated quality assessment platforms that set the standard for how AI outputs are validated at enterprise scale
• Provide technical leadership across Uber AI Solutions—collaborating with engineering, product, and data science leadership to align technical roadmaps with business strategy
• Mentor and develop engineering talent: lead and mentor Staff, Senior, and mid-level ML engineers, establishing best practices for ML system design, experimentation, and deployment while raising technical standards across the organization
• Enable cross-functional impact: partner with ML Ops, backend, and platform teams to ensure solutions demonstrate craftsmanship, reliability, and scalability while managing upstream and downstream dependencies

Basic Qualifications:

• 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

Preferred Qualifications:

• 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

For Sunnyvale, CA-based roles: The base salary range for this role is USD$267,000 per year - USD$297,000 per year.

You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.

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 fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

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.